{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,15]],"date-time":"2026-10-15T16:25:42Z","timestamp":1792081542521,"version":"4.4.0"},"reference-count":112,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2026,1,12]],"date-time":"2026-01-12T00:00:00Z","timestamp":1768176000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,1,12]],"date-time":"2026-01-12T00:00:00Z","timestamp":1768176000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Sci. China Inf. Sci."],"published-print":{"date-parts":[[2026,2]]},"DOI":"10.1007\/s11432-025-4631-2","type":"journal-article","created":{"date-parts":[[2026,1,21]],"date-time":"2026-01-21T09:43:04Z","timestamp":1768988584000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["Towards versatile multimedia quality assessment for visual communications"],"prefix":"10.1007","volume":"69","author":[{"given":"Zicheng","family":"Zhang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ziheng","family":"Jia","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chunyi","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yingjie","family":"Zhou","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaohong","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiongkuo","family":"Min","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Guangtao","family":"Zhai","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,1,12]]},"reference":[{"key":"4631_CR1","first-page":"3","volume":"21","author":"Y Zhou","year":"2023","unstructured":"Zhou Y, Zhang Z, Sun W, et al. Perceptual quality assessment for point clouds: a survey. ZTE Commun, 2023, 21: 3\u201316","journal-title":"ZTE Commun"},{"key":"4631_CR2","first-page":"1","volume":"21","author":"Z Zhang","year":"2025","unstructured":"Zhang Z, Zhou Y, Li C, et al. Quality assessment in the era of large models: a survey. ACM Trans Multimedia Comput Commun Appl, 2025, 21: 1\u201331","journal-title":"ACM Trans Multimedia Comput Commun Appl"},{"key":"4631_CR3","first-page":"1","volume":"14","author":"L Skorin-Kapov","year":"2018","unstructured":"Skorin-Kapov L, Varela M, Ho\u00dffeld T, et al. A survey of emerging concepts and challenges for QoE management of multimedia services. ACM Trans Multimedia Comput Commun Appl, 2018, 14: 1\u201329","journal-title":"ACM Trans Multimedia Comput Commun Appl"},{"key":"4631_CR4","doi-asserted-by":"publisher","first-page":"211301","DOI":"10.1007\/s11432-024-4133-3","volume":"67","author":"X K Min","year":"2024","unstructured":"Min X K, Duan H Y, Sun W, et al. Perceptual video quality assessment: a survey. Sci China Inf Sci, 2024, 67: 211301","journal-title":"Sci China Inf Sci"},{"key":"4631_CR5","first-page":"1","volume-title":"Proceedings of the IEEE International Conference on Acoustics, Hyderabad","author":"R Wang","year":"2025","unstructured":"Wang R, Li W, Liu X, et al. Hazeclip: towards language guided real-world image dehazing. In: Proceedings of the IEEE International Conference on Acoustics, Hyderabad, 2025. 1\u20135"},{"key":"4631_CR6","first-page":"1","volume-title":"Proceedings of the IEEE International Conference on Multimedia and Expo (ICME)","author":"Z Zhang","year":"2021","unstructured":"Zhang Z, Sun W, Min X, et al. A no-reference evaluation metric for low-light image enhancement. In: Proceedings of the IEEE International Conference on Multimedia and Expo (ICME), 2021. 1\u20136"},{"key":"4631_CR7","doi-asserted-by":"publisher","first-page":"1732","DOI":"10.1109\/TIP.2018.2878326","volume":"28","author":"C Zhang","year":"2018","unstructured":"Zhang C, Cheng W, Hirakawa K. Corrupted reference image quality assessment of denoised images. IEEE Trans Image Process, 2018, 28: 1732\u20131747","journal-title":"IEEE Trans Image Process"},{"key":"4631_CR8","doi-asserted-by":"publisher","first-page":"103696","DOI":"10.1016\/j.jvcir.2022.103696","volume":"90","author":"Z Zhang","year":"2023","unstructured":"Zhang Z, Sun W, Wu W, et al. Perceptual quality assessment for fine-grained compressed images. J Visual Commun Image Represent, 2023, 90: 103696","journal-title":"J Visual Commun Image Represent"},{"key":"4631_CR9","doi-asserted-by":"publisher","first-page":"4297","DOI":"10.1145\/3474085.3475569","volume-title":"Proceedings of the 29th ACM International Conference on Multimedia","author":"Y Li","year":"2021","unstructured":"Li Y, Wang S, Zhang X, et al. Quality assessment of end-to-end learned image compression: the benchmark and objective measure. In: Proceedings of the 29th ACM International Conference on Multimedia, 2021. 4297\u20134305"},{"key":"4631_CR10","doi-asserted-by":"publisher","first-page":"7618","DOI":"10.1109\/TCSVT.2022.3186894","volume":"32","author":"Z Zhang","year":"2022","unstructured":"Zhang Z, Sun W, Min X, et al. No-reference quality assessment for 3D colored point cloud and mesh models. IEEE Trans Circ Syst Video Technol, 2022, 32: 7618\u20137631","journal-title":"IEEE Trans Circ Syst Video Technol"},{"key":"4631_CR11","first-page":"34892","volume-title":"Proceedings of the Advances in Neural Information Processing Systems","author":"H Liu","year":"2023","unstructured":"Liu H, Li C, Wu Q, et al. Visual instruction tuning. In: Proceedings of the Advances in Neural Information Processing Systems, 2023. 34892\u201334916"},{"key":"4631_CR12","unstructured":"Zhang Z, Wu H, Zhou Y, et al. LMM-PCQA: assisting point cloud quality assessment with LMM. ArXiv:2404.18203"},{"key":"4631_CR13","unstructured":"Wu H, Zhang Z, Zhang W, et al. Q-align: teaching LMMs for visual scoring via discrete text-defined levels. ArXiv:2312.17090"},{"key":"4631_CR14","first-page":"6201","volume-title":"Proceedings of the ICCV","author":"C Feichtenhofer","year":"2019","unstructured":"Feichtenhofer C, Fan H, Malik J, et al. Slowfast networks for video recognition. In: Proceedings of the ICCV, 2019. 6201\u20136210"},{"key":"4631_CR15","volume-title":"Proceedings of the Advances in Neural Information Processing Systems","author":"C R Qi","year":"2017","unstructured":"Qi C R, Yi L, Su H, et al. Pointnet++: deep hierarchical feature learning on point sets in a metric space. In: Proceedings of the Advances in Neural Information Processing Systems, 2017"},{"key":"4631_CR16","first-page":"14143","volume-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)","author":"H Zhu","year":"2020","unstructured":"Zhu H, Li L, Wu J, et al. MetaIQA: deep meta-learning for no-reference image quality assessment. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2020. 14143\u201314152"},{"key":"4631_CR17","doi-asserted-by":"publisher","first-page":"39","DOI":"10.1109\/TCYB.2015.2392129","volume":"46","author":"L Li","year":"2015","unstructured":"Li L, Lin W, Wang X, et al. No-reference image blur assessment based on discrete orthogonal moments. IEEE Trans Cybern, 2015, 46: 39\u201350","journal-title":"IEEE Trans Cybern"},{"key":"4631_CR18","doi-asserted-by":"publisher","first-page":"39","DOI":"10.1109\/TCYB.2015.2392129","volume":"46","author":"L Li","year":"2015","unstructured":"Li L, Lin W, Wang X, et al. No-reference image blur assessment based on discrete orthogonal moments. IEEE Trans Cybern, 2015, 46: 39\u201350","journal-title":"IEEE Trans Cybern"},{"key":"4631_CR19","doi-asserted-by":"publisher","first-page":"1085","DOI":"10.1109\/TMM.2016.2545398","volume":"18","author":"L Li","year":"2016","unstructured":"Li L, Wu D, Wu J, et al. Image sharpness assessment by sparse representation. IEEE Trans Multimedia, 2016, 18: 1085\u20131097","journal-title":"IEEE Trans Multimedia"},{"key":"4631_CR20","doi-asserted-by":"publisher","first-page":"3650","DOI":"10.1109\/TIP.2021.3064195","volume":"30","author":"J Ma","year":"2021","unstructured":"Ma J, Wu J, Li L, et al. Blind image quality assessment with active inference. IEEE Trans Image Process, 2021, 30: 3650\u20133663","journal-title":"IEEE Trans Image Process"},{"key":"4631_CR21","first-page":"6732","volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","author":"N Chahine","year":"2024","unstructured":"Chahine N, Conde M V, Carfora D, et al. Deep portrait quality assessment. a ntire 2024 challenge survey. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 2024. 6732\u20136744"},{"key":"4631_CR22","doi-asserted-by":"publisher","first-page":"10431","DOI":"10.1145\/3664647.3681561","volume-title":"Proceedings of the 32nd ACM International Conference on Multimedia","author":"Z Wan","year":"2024","unstructured":"Wan Z, Yang Q, Li Z, et al. Dual-stream perception-driven blind quality assessment for stereoscopic omnidirectional images. In: Proceedings of the 32nd ACM International Conference on Multimedia, 2024. 10431\u201310439"},{"key":"4631_CR23","doi-asserted-by":"publisher","first-page":"7196","DOI":"10.1109\/TCSVT.2025.3538511","volume":"35","author":"Z Wan","year":"2025","unstructured":"Wan Z, Yan X, Li Z, et al. No-reference stereoscopic omnidirectional image quality assessment via a binocular viewport hypergraph convolutional network. IEEE Trans Circ Syst Video Technol, 2025, 35: 7196\u20137209","journal-title":"IEEE Trans Circ Syst Video Technol"},{"key":"4631_CR24","doi-asserted-by":"publisher","first-page":"2024","DOI":"10.1109\/TMM.2019.2950533","volume":"22","author":"Z Wan","year":"2019","unstructured":"Wan Z, Gu K, Zhao D. Reduced reference stereoscopic image quality assessment using sparse representation and natural scene statistics. IEEE Trans Multimedia, 2019, 22: 2024\u20132037","journal-title":"IEEE Trans Multimedia"},{"key":"4631_CR25","volume-title":"Aibench: towards trustworthy evaluation under the 45\u00b0 law","author":"Z Zhang","year":"2025","unstructured":"Zhang Z, Wang J, Guo Y, et al. Aibench: towards trustworthy evaluation under the 45\u00b0 law. 2025. https:\/\/aiben.ch\/"},{"key":"4631_CR26","volume-title":"Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing","author":"Z Wang","year":"2002","unstructured":"Wang Z, Bovik A C, Lu L. Why is image quality assessment so difficult? In: Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing, 2002"},{"key":"4631_CR27","doi-asserted-by":"publisher","first-page":"193","DOI":"10.1109\/JSTSP.2009.2015374","volume":"3","author":"A K Moorthy","year":"2009","unstructured":"Moorthy A K, Bovik A C. Visual importance pooling for image quality assessment. IEEE J Sel Top Signal Process, 2009, 3: 193\u2013201","journal-title":"IEEE J Sel Top Signal Process"},{"key":"4631_CR28","doi-asserted-by":"publisher","first-page":"513","DOI":"10.1109\/LSP.2010.2043888","volume":"17","author":"A K Moorthy","year":"2010","unstructured":"Moorthy A K, Bovik A C. A two-step framework for constructing blind image quality indices. IEEE Signal Process Lett, 2010, 17: 513\u2013516","journal-title":"IEEE Signal Process Lett"},{"key":"4631_CR29","doi-asserted-by":"publisher","first-page":"149","DOI":"10.1016\/j.proeng.2013.09.086","volume":"64","author":"K De","year":"2013","unstructured":"De K, Masilamani V. Image sharpness measure for blurred images in frequency domain. Procedia Eng, 2013, 64: 149\u2013158","journal-title":"Procedia Eng"},{"key":"4631_CR30","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.image.2015.10.005","volume":"40","author":"L Liu","year":"2016","unstructured":"Liu L, Hua Y, Zhao Q, et al. Blind image quality assessment by relative gradient statistics and Adaboosting neural network. Signal Process-Image Commun, 2016, 40: 1\u201315","journal-title":"Signal Process-Image Commun"},{"key":"4631_CR31","doi-asserted-by":"publisher","first-page":"355","DOI":"10.1007\/s11760-017-1166-8","volume":"12","author":"S Bianco","year":"2018","unstructured":"Bianco S, Celona L, Napoletano P, et al. On the use of deep learning for blind image quality assessment. SIViP, 2018, 12: 355\u2013362","journal-title":"SIViP"},{"key":"4631_CR32","doi-asserted-by":"publisher","first-page":"917","DOI":"10.1109\/TCSVT.2019.2898732","volume":"30","author":"H G Kim","year":"2020","unstructured":"Kim H G, Lim H T, Ro Y M. Deep virtual reality image quality assessment with human perception guider for omnidirectional image. IEEE Trans Circ Syst Video Technol, 2020, 30: 917\u2013928","journal-title":"IEEE Trans Circ Syst Video Technol"},{"key":"4631_CR33","doi-asserted-by":"publisher","first-page":"64","DOI":"10.1109\/JSTSP.2019.2955024","volume":"14","author":"W Sun","year":"2019","unstructured":"Sun W, Min X, Zhai G, et al. MC360IQA: a multi-channel CNN for blind 360-degree image quality assessment. IEEE J Sel Top Signal Process, 2019, 14: 64\u201377","journal-title":"IEEE J Sel Top Signal Process"},{"key":"4631_CR34","volume-title":"Proceedings of the CVPR","author":"Y Fang","year":"2020","unstructured":"Fang Y, Zhu H, Zeng Y, et al. Perceptual quality assessment of smartphone photography. In: Proceedings of the CVPR, 2020"},{"key":"4631_CR35","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3507901","volume":"54","author":"T Schlett","year":"2022","unstructured":"Schlett T, Rathgeb C, Henniger O, et al. Face image quality assessment: a literature survey. ACM Comput Surv, 2022, 54: 1\u201349","journal-title":"ACM Comput Surv"},{"key":"4631_CR36","first-page":"433","volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","author":"M Cheon","year":"2021","unstructured":"Cheon M, Yoon S J, Kang B, et al. Perceptual image quality assessment with transformers. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 2021. 433\u2013442"},{"key":"4631_CR37","first-page":"1","volume-title":"Proceedings of the 2021 IEEE International Conference on Multimedia and Expo (ICME)","author":"Z Zhang","year":"2021","unstructured":"Zhang Z, Sun W, Min X, et al. A no-reference evaluation metric for low-light image enhancement. In: Proceedings of the 2021 IEEE International Conference on Multimedia and Expo (ICME), 2021. 1\u20136"},{"key":"4631_CR38","doi-asserted-by":"publisher","first-page":"406","DOI":"10.1109\/TBC.2022.3221689","volume":"69","author":"W Lu","year":"2022","unstructured":"Lu W, Sun W, Min X, et al. Deep neural network for blind visual quality assessment of 4K content. IEEE Trans Broadcast, 2022, 69: 406\u2013421","journal-title":"IEEE Trans Broadcast"},{"key":"4631_CR39","doi-asserted-by":"publisher","first-page":"3543","DOI":"10.1007\/s13042-022-01611-w","volume":"13","author":"J Cao","year":"2022","unstructured":"Cao J, Wu W, Wang R, et al. No-reference image quality assessment by using convolutional neural networks via object detection. Int J Mach Learn Cyber, 2022, 13: 3543\u20133554","journal-title":"Int J Mach Learn Cyber"},{"key":"4631_CR40","first-page":"6415","volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","author":"X Li","year":"2024","unstructured":"Li X, Yuan K, Pei Y, et al. Ntire 2024 challenge on short-form ugc video quality assessment: methods and results. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 2024. 6415\u20136431"},{"key":"4631_CR41","first-page":"5826","volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","author":"M V Conde","year":"2024","unstructured":"Conde M V, Zadtootaghaj S, Barman N, et al. Ais 2024 challenge on video quality assessment of user-generated content: methods and results. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 2024. 5826\u20135837"},{"key":"4631_CR42","first-page":"4278","volume-title":"Proceedings of the IEEE International Conference on Image Processing (ICIP)","author":"Z Zhang","year":"2022","unstructured":"Zhang Z, Lu W, Sun W, et al. Surveillance video quality assessment based on quality related retraining. In: Proceedings of the IEEE International Conference on Image Processing (ICIP), 2022. 4278\u20134282"},{"key":"4631_CR43","doi-asserted-by":"publisher","first-page":"121","DOI":"10.1016\/S0923-5965(03)00076-6","volume":"19","author":"Z Wang","year":"2004","unstructured":"Wang Z, Lu L, Bovik A C. Video quality assessment based on structural distortion measurement. Signal Process-Image Commun, 2004, 19: 121\u2013132","journal-title":"Signal Process-Image Commun"},{"key":"4631_CR44","first-page":"I-869","volume-title":"Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing","author":"K Seshadrinathan","year":"2007","unstructured":"Seshadrinathan K, Bovik A C. A structural similarity metric for video based on motion models. In: Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing, 2007. I-869"},{"key":"4631_CR45","doi-asserted-by":"publisher","first-page":"B61","DOI":"10.1364\/JOSAA.24.000B61","volume":"24","author":"Z Wang","year":"2007","unstructured":"Wang Z, Li Q. Video quality assessment using a statistical model of human visual speed perception. J Opt Soc Am A, 2007, 24: B61","journal-title":"J Opt Soc Am A"},{"key":"4631_CR46","doi-asserted-by":"publisher","first-page":"1316","DOI":"10.1109\/TMM.2008.2004910","volume":"10","author":"G Zhai","year":"2008","unstructured":"Zhai G, Cai J, Lin W, et al. Cross-dimensional perceptual quality assessment for low bit-rate videos. IEEE Trans Multimedia, 2008, 10: 1316\u20131324","journal-title":"IEEE Trans Multimedia"},{"key":"4631_CR47","doi-asserted-by":"publisher","first-page":"253","DOI":"10.1109\/JSTSP.2009.2014806","volume":"3","author":"A Ninassi","year":"2009","unstructured":"Ninassi A, Le Meur O, Le Callet P, et al. Considering temporal variations of spatial visual distortions in video quality assessment. IEEE J Sel Top Signal Process, 2009, 3: 253\u2013265","journal-title":"IEEE J Sel Top Signal Process"},{"key":"4631_CR48","first-page":"2505","volume-title":"Proceedings of the 18th IEEE International Conference on Image Processing","author":"P V Vu","year":"2011","unstructured":"Vu P V, Vu C T, Chandler D M. A spatiotemporal most-apparent-distortion model for video quality assessment. In: Proceedings of the 18th IEEE International Conference on Image Processing, 2011. 2505\u20132508"},{"key":"4631_CR49","doi-asserted-by":"publisher","first-page":"15185","DOI":"10.1109\/TPAMI.2023.3319332","volume":"45","author":"H Wu","year":"2023","unstructured":"Wu H, Chen C, Liao L, et al. Neighbourhood representative sampling for efficient end-to-end video quality assessment. IEEE Trans Pattern Anal Mach Intell, 2023, 45: 15185\u201315202","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"4631_CR50","volume-title":"Proceedings of the European Conference of Computer Vision (ECCV)","author":"H Wu","year":"2022","unstructured":"Wu H, Chen C, Hou J, et al. Fast-VQA: efficient end-to-end video quality assessment with fragment sampling. In: Proceedings of the European Conference of Computer Vision (ECCV), 2022"},{"key":"4631_CR51","volume-title":"Proceedings of the ICCV","author":"H Wu","year":"2023","unstructured":"Wu H, Zhang E, Liao L, et al. Exploring video quality assessment on user generated contents from aesthetic and technical perspectives. In: Proceedings of the ICCV, 2023"},{"key":"4631_CR52","unstructured":"Zhou X, Liu X, Dong Y, et al. Light-VQA+: a video quality assessment model for exposure correction with vision-language guidance. ArXiv:2405.03333"},{"key":"4631_CR53","doi-asserted-by":"publisher","first-page":"1088","DOI":"10.1145\/3581783.3611923","volume-title":"Proceedings of the 31st ACM International Conference on Multimedia","author":"Y Dong","year":"2023","unstructured":"Dong Y, Liu X, Gao Y, et al. Light-VQA: a multi-dimensional quality assessment model for low-light video enhancement. In: Proceedings of the 31st ACM International Conference on Multimedia, 2023. 1088\u20131097"},{"key":"4631_CR54","first-page":"1","volume-title":"Proceedings of the IEEE International Conference on Multimedia and Expo (ICME)","author":"E Alexiou","year":"2018","unstructured":"Alexiou E, Ebrahimi T. Point cloud quality assessment metric based on angular similarity. In: Proceedings of the IEEE International Conference on Multimedia and Expo (ICME), 2018. 1\u20136"},{"key":"4631_CR55","first-page":"3182","volume-title":"Proceedings of the IEEE International Conference on Image Processing (ICIP)","author":"H Su","year":"2019","unstructured":"Su H, Duanmu Z, Liu W, et al. Perceptual quality assessment of 3D point clouds. In: Proceedings of the IEEE International Conference on Image Processing (ICIP), 2019. 3182\u20133186"},{"key":"4631_CR56","first-page":"3443","volume-title":"Proceedings of the IEEE International Conference on Image Processing (ICIP)","author":"R Diniz","year":"2020","unstructured":"Diniz R, Freitas P G, Farias M C. Multi-distance point cloud quality assessment. In: Proceedings of the IEEE International Conference on Image Processing (ICIP), 2020. 3443\u20133447"},{"key":"4631_CR57","doi-asserted-by":"publisher","first-page":"1230","DOI":"10.1145\/3474085.3475294","volume-title":"Proceedings of the 29th ACM International Conference on Multimedia","author":"Y Zhang","year":"2021","unstructured":"Zhang Y, Yang Q, Xu Y. Ms-graphsim: inferring point cloud quality via multiscale graph similarity. In: Proceedings of the 29th ACM International Conference on Multimedia, 2021. 1230\u20131238"},{"key":"4631_CR58","first-page":"1","volume-title":"Proceedings of the IEEE International Conference on Multimedia & Expo Workshops (ICMEW)","author":"Z Zhang","year":"2021","unstructured":"Zhang Z, Sun W, Min X, et al. A no-reference visual quality metric for 3D color meshes. In: Proceedings of the IEEE International Conference on Multimedia & Expo Workshops (ICMEW), 2021. 1\u20136"},{"key":"4631_CR59","first-page":"21179","volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","author":"Q Yang","year":"2022","unstructured":"Yang Q, Liu Y, Chen S, et al. No-reference point cloud quality assessment via domain adaptation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 2022. 21179\u201321188"},{"key":"4631_CR60","doi-asserted-by":"publisher","first-page":"927","DOI":"10.1109\/TMM.2023.3340894","volume":"27","author":"Z Zhang","year":"2025","unstructured":"Zhang Z, Sun W, Zhu Y, et al. Evaluating point cloud from moving camera videos: a no-reference metric. IEEE Trans Multimedia, 2025, 27: 927\u2013939","journal-title":"IEEE Trans Multimedia"},{"key":"4631_CR61","first-page":"1","volume-title":"Proceedings of the 24th International Workshop on Multimedia Signal Processing (MMSP)","author":"Y Fan","year":"2022","unstructured":"Fan Y, Zhang Z, Sun W, et al. A no-reference quality assessment metric for point cloud based on captured video sequences. In: Proceedings of the 24th International Workshop on Multimedia Signal Processing (MMSP), 2022. 1\u20135"},{"key":"4631_CR62","unstructured":"Zhang Z, Sun W, Min X, et al. MM-PCQA: multi-modal learning for no-reference point cloud quality assessment. ArXiv:2209.00244"},{"key":"4631_CR63","first-page":"2483","volume-title":"Proceedings of the IEEE International Conference on Multimedia and Expo (ICME)","author":"Z Zhang","year":"2023","unstructured":"Zhang Z, Sun W, Zhou Y, et al. EEP-3DQA: efficient and effective projection-based 3D model quality assessment. In: Proceedings of the IEEE International Conference on Multimedia and Expo (ICME), 2023. 2483\u20132488"},{"key":"4631_CR64","first-page":"1","volume":"20","author":"Z Zhang","year":"2024","unstructured":"Zhang Z, Sun W, Wu H, et al. GMS-3DQA: projection-based grid mini-patch sampling for 3D model quality assessment. ACM Trans Multimedia Comput Commun Appl, 2024, 20: 1\u201319","journal-title":"ACM Trans Multimedia Comput Commun Appl"},{"key":"4631_CR65","first-page":"2965","volume-title":"Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","author":"Z Zhang","year":"2024","unstructured":"Zhang Z, Zhou Y, Li C, et al. A reduced-reference quality assessment metric for textured mesh digital humans. In: Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2024. 2965\u20132969"},{"key":"4631_CR66","doi-asserted-by":"publisher","first-page":"102540","DOI":"10.1016\/j.displa.2023.102540","volume":"80","author":"S Chen","year":"2023","unstructured":"Chen S, Zhang Z, Zhou Y, et al. A no-reference quality assessment metric for dynamic 3D digital human. Displays, 2023, 80: 102540","journal-title":"Displays"},{"key":"4631_CR67","unstructured":"OpenAI. GPT-4 technical report. ArXiv:2303.08774"},{"key":"4631_CR68","unstructured":"Chung H W, Hou L, Longpre S, et al. Scaling instruction-finetuned language models. ArXiv:2210.11416"},{"key":"4631_CR69","unstructured":"Touvron H, Lavril T, Izacard G, et al. Llama: open and efficient foundation language models. ArXiv:2302.13971"},{"key":"4631_CR70","volume-title":"Proceedings of the International Conference on Machine Learning","author":"A Radford","year":"2021","unstructured":"Radford A, Kim J W, Hallacy C, et al. Learning transferable visual models from natural language supervision. In: Proceedings of the International Conference on Machine Learning, 2021"},{"key":"4631_CR71","unstructured":"Li B, Zhang Y, Chen L, et al. Otter: a multi-modal model with in-context instruction tuning. ArXiv:2305.03726"},{"key":"4631_CR72","unstructured":"Gao P, Han J, Zhang R, et al. Llama-adapter v2: parameter-efficient visual instruction model. ArXiv:2304.15010"},{"key":"4631_CR73","volume-title":"Proceedings of the Advances in Neural Information Processing Systems","author":"W Dai","year":"2023","unstructured":"Dai W, Li J, Li D, et al. Instructblip: towards general-purpose vision-language models with instruction tuning. In: Proceedings of the Advances in Neural Information Processing Systems, 2023"},{"key":"4631_CR74","unstructured":"Zhang P, Dong X, Wang B, et al. Internlm-xcomposer: a vision-language large model for advanced text-image comprehension and composition. ArXiv:2309.15112"},{"key":"4631_CR75","unstructured":"Awadalla A, Gao I, Gardner J, et al. Openflamingo: an open-source framework for training large autoregressive vision-language models. ArXiv:2308.01390"},{"key":"4631_CR76","first-page":"19730","volume-title":"Proceedings of the International Conference on Machine Learning","author":"J Li","year":"2023","unstructured":"Li J, Li D, Savarese S, et al. Blip-2: bootstrapping language-image pre-training with frozen image encoders and large language models. In: Proceedings of the International Conference on Machine Learning, 2023. 19730\u201319742"},{"key":"4631_CR77","volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","author":"H Liu","year":"2023","unstructured":"Liu H, Li C, Li Y, et al. Improved baselines with visual instruction tuning. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 2023"},{"key":"4631_CR78","volume-title":"LlaVA-NeXT: improved reasoning, OCR, and world knowledge","author":"H Liu","year":"2024","unstructured":"Liu H, Li C, Li Y, et al. LlaVA-NeXT: improved reasoning, OCR, and world knowledge. 2024. https:\/\/llava-vl.github.io\/blog\/2024-01-30-llava-next\/"},{"key":"4631_CR79","unstructured":"Ye Q, Xu H, Ye J, et al. Mplug-owl2: revolutionizing multi-modal large language model with modality collaboration. ArXiv:2311.04257"},{"key":"4631_CR80","series-title":"ITU-R Rec. BT.500","volume-title":"Recommendation 500-10: methodology for the subjective assessment of the quality of television pictures","author":"ITU","year":"2000","unstructured":"ITU. Recommendation 500-10: methodology for the subjective assessment of the quality of television pictures. ITU-R Rec. BT.500, 2000"},{"key":"4631_CR81","doi-asserted-by":"publisher","first-page":"372","DOI":"10.1109\/TIP.2015.2500021","volume":"25","author":"D Ghadiyaram","year":"2016","unstructured":"Ghadiyaram D, Bovik A C. Massive online crowdsourced study of subjective and objective picture quality. IEEE Trans Image Process, 2016, 25: 372\u2013387","journal-title":"IEEE Trans Image Process"},{"key":"4631_CR82","doi-asserted-by":"publisher","first-page":"4041","DOI":"10.1109\/TIP.2020.2967829","volume":"29","author":"V Hosu","year":"2020","unstructured":"Hosu V, Lin H, Sziranyi T, et al. KonIQ-10k: an ecologically valid database for deep learning of blind image quality assessment. IEEE Trans Image Process, 2020, 29: 4041\u20134056","journal-title":"IEEE Trans Image Process"},{"key":"4631_CR83","doi-asserted-by":"publisher","first-page":"64","DOI":"10.1145\/2812802","volume":"59","author":"B Thomee","year":"2016","unstructured":"Thomee B, Shamma D A, Friedland G, et al. Yfcc100m: the new data in multimedia research. Commun ACM, 2016, 59: 64\u201373","journal-title":"Commun ACM"},{"key":"4631_CR84","first-page":"1","volume-title":"Proceedings of the QoMEX","author":"H Lin","year":"2019","unstructured":"Lin H, Hosu V, Saupe D. Kadid-10k: a large-scale artificially distorted iqa database. In: Proceedings of the QoMEX, 2019. 1\u20133"},{"key":"4631_CR85","doi-asserted-by":"publisher","first-page":"6833","DOI":"10.1109\/TCSVT.2023.3319020","volume":"34","author":"C Li","year":"2024","unstructured":"Li C, Zhang Z, Wu H, et al. AGIQA-3K: an open database for AI-generated image quality assessment. IEEE Trans Circ Syst Video Technol, 2024, 34: 6833\u20136846","journal-title":"IEEE Trans Circ Syst Video Technol"},{"key":"4631_CR86","first-page":"1","volume-title":"Proceedings of the QoMEX","author":"V Hosu","year":"2017","unstructured":"Hosu V, Hahn F, Jenadeleh M, et al. The konstanz natural video database (konvid-1k). In: Proceedings of the QoMEX, 2017. 1\u20136"},{"key":"4631_CR87","doi-asserted-by":"publisher","first-page":"612","DOI":"10.1109\/TIP.2018.2869673","volume":"28","author":"Z Sinno","year":"2019","unstructured":"Sinno Z, Bovik A C. Large-scale study of perceptual video quality. IEEE Trans Image Process, 2019, 28: 612\u2013627","journal-title":"IEEE Trans Image Process"},{"key":"4631_CR88","volume-title":"Proceedings of the CVPR","author":"Z Ying","year":"2021","unstructured":"Ying Z, Mandal M, Ghadiyaram D, et al. Patch-vq: \u2018patching up\u2019 the video quality problem. In: Proceedings of the CVPR, 2021"},{"key":"4631_CR89","doi-asserted-by":"publisher","first-page":"3877","DOI":"10.1109\/TMM.2020.3033117","volume":"23","author":"Q Yang","year":"2020","unstructured":"Yang Q, Chen H, Ma Z, et al. Predicting the perceptual quality of point cloud: a 3D-to-2D projection-based exploration. IEEE Trans Multimedia, 2020, 23: 3877\u20133891","journal-title":"IEEE Trans Multimedia"},{"key":"4631_CR90","doi-asserted-by":"publisher","first-page":"3642","DOI":"10.1109\/TVCG.2022.3167151","volume":"29","author":"Q Liu","year":"2023","unstructured":"Liu Q, Su H, Duanmu Z, et al. Perceptual quality assessment of colored 3D point clouds. IEEE Trans Visual Comput Graphics, 2023, 29: 3642\u20133655","journal-title":"IEEE Trans Visual Comput Graphics"},{"key":"4631_CR91","doi-asserted-by":"publisher","first-page":"6623","DOI":"10.1109\/TIP.2021.3096060","volume":"30","author":"Q Liu","year":"2021","unstructured":"Liu Q, Yuan H, Hamzaoui R, et al. Reduced reference perceptual quality model with application to rate control for video-based point cloud compression. IEEE Trans Image Process, 2021, 30: 6623\u20136636","journal-title":"IEEE Trans Image Process"},{"key":"4631_CR92","doi-asserted-by":"publisher","first-page":"4695","DOI":"10.1109\/TIP.2012.2214050","volume":"21","author":"A Mittal","year":"2012","unstructured":"Mittal A, Moorthy A K, Bovik A C. No-reference image quality assessment in the spatial domain. IEEE Trans Image Process, 2012, 21: 4695\u20134708","journal-title":"IEEE Trans Image Process"},{"key":"4631_CR93","doi-asserted-by":"publisher","first-page":"209","DOI":"10.1109\/LSP.2012.2227726","volume":"20","author":"A Mittal","year":"2013","unstructured":"Mittal A, Soundararajan R, Bovik A C. Making a \u201ccompletely blind\u201d image quality analyzer. IEEE Signal Process Lett, 2013, 20: 209\u2013212","journal-title":"IEEE Signal Process Lett"},{"key":"4631_CR94","doi-asserted-by":"publisher","first-page":"3998","DOI":"10.1109\/TIP.2018.2831899","volume":"27","author":"H Talebi","year":"2018","unstructured":"Talebi H, Milanfar P. NIMA: neural image assessment. IEEE Trans Image Process, 2018, 27: 3998\u20134011","journal-title":"IEEE Trans Image Process"},{"key":"4631_CR95","doi-asserted-by":"publisher","first-page":"36","DOI":"10.1109\/TCSVT.2018.2886771","volume":"30","author":"W Zhang","year":"2020","unstructured":"Zhang W, Ma K, Yan J, et al. Blind image quality assessment using a deep bilinear convolutional neural network. IEEE Trans Circ Syst Video Technol, 2020, 30: 36\u201347","journal-title":"IEEE Trans Circ Syst Video Technol"},{"key":"4631_CR96","volume-title":"Proceedings of the CVPR","author":"S Su","year":"2020","unstructured":"Su S, Yan Q, Zhu Y, et al. Blindly assess image quality in the wild guided by a self-adaptive hyper network. In: Proceedings of the CVPR, 2020"},{"key":"4631_CR97","first-page":"5148","volume-title":"Proceedings of the ICCV","author":"J Ke","year":"2021","unstructured":"Ke J, Wang Q, Wang Y, et al. MUSIQ: multi-scale image quality transformer. In: Proceedings of the ICCV, 2021. 5148\u20135157"},{"key":"4631_CR98","volume-title":"Proceedings of the AAAI Conference on Artificial Intelligence","author":"J Wang","year":"2022","unstructured":"Wang J, Chan K C K, Loy C C. Exploring clip for assessing the look and feel of images. In: Proceedings of the AAAI Conference on Artificial Intelligence, 2022"},{"key":"4631_CR99","volume-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition","author":"W Zhang","year":"2023","unstructured":"Zhang W, Zhai G, Wei Y, et al. Blind image quality assessment via vision-language correspondence: a multitask learning perspective. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2023"},{"key":"4631_CR100","doi-asserted-by":"publisher","first-page":"5923","DOI":"10.1109\/TIP.2019.2923051","volume":"28","author":"J Korhonen","year":"2019","unstructured":"Korhonen J. Two-level approach for no-reference consumer video quality assessment. IEEE Trans Image Process, 2019, 28: 5923\u20135938","journal-title":"IEEE Trans Image Process"},{"key":"4631_CR101","volume-title":"Proceedings of the ACM MM","author":"D Li","year":"2019","unstructured":"Li D, Jiang T, Jiang M. Quality assessment of in-the-wild videos. In: Proceedings of the ACM MM, 2019"},{"key":"4631_CR102","doi-asserted-by":"publisher","first-page":"4449","DOI":"10.1109\/TIP.2021.3072221","volume":"30","author":"Z Tu","year":"2021","unstructured":"Tu Z, Wang Y, Birkbeck N, et al. UGC-VQA: benchmarking blind video quality assessment for user generated content. IEEE Trans Image Process, 2021, 30: 4449\u20134464","journal-title":"IEEE Trans Image Process"},{"key":"4631_CR103","doi-asserted-by":"publisher","first-page":"5944","DOI":"10.1109\/TCSVT.2022.3164467","volume":"32","author":"B Li","year":"2022","unstructured":"Li B, Zhang W, Tian M, et al. Blindly assess quality of in-the-wild videos via quality-aware pre-training and motion perception. IEEE Trans Circ Syst Video Technol, 2022, 32: 5944\u20135958","journal-title":"IEEE Trans Circ Syst Video Technol"},{"key":"4631_CR104","doi-asserted-by":"publisher","first-page":"4840","DOI":"10.1109\/TCSVT.2023.3249741","volume":"33","author":"H Wu","year":"2023","unstructured":"Wu H, Chen C, Liao L, et al. DisCoVQA: temporal distortion-content transformers for video quality assessment. IEEE Trans Circ Syst Video Technol, 2023, 33: 4840\u20134854","journal-title":"IEEE Trans Circ Syst Video Technol"},{"key":"4631_CR105","unstructured":"Sun W, Min X, Lu W, et al. A deep learning based no-reference quality assessment model for ugc videos. ArXiv:2204.14047"},{"key":"4631_CR106","volume-title":"Proceedings of the ECCV","author":"H Wu","year":"2022","unstructured":"Wu H, Chen C, Hou J, et al. Fast-VQA: efficient end-to-end video quality assessment with fragment sampling. In: Proceedings of the ECCV, 2022"},{"key":"4631_CR107","volume-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)","author":"Q Yang","year":"2022","unstructured":"Yang Q, Liu Y, Chen S, et al. No-reference point cloud quality assessment via domain adaptation. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2022"},{"key":"4631_CR108","first-page":"1","volume":"19","author":"Y Liu","year":"2023","unstructured":"Liu Y, Yang Q, Xu Y, et al. Point cloud quality assessment: dataset construction and learning-based no-reference metric. ACM Trans Multimedia Comput Commun Appl, 2023, 19: 1\u201326","journal-title":"ACM Trans Multimedia Comput Commun Appl"},{"key":"4631_CR109","unstructured":"Touvron H, Martin L, Stone K, et al. Llama 2: open foundation and fine-tuned chat models. 2023. ArXiv:2307.09288"},{"key":"4631_CR110","unstructured":"Kay W, Carreira J, Simonyan K, et al. The kinetics human action video dataset. 2017. ArXiv:1705.06950"},{"key":"4631_CR111","first-page":"1912","volume-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)","author":"Z Wu","year":"2015","unstructured":"Wu Z, Song S, Khosla A, et al. 3D shapenets: a deep representation for volumetric shapes. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015. 1912\u20131920"},{"key":"4631_CR112","doi-asserted-by":"publisher","first-page":"3440","DOI":"10.1109\/TIP.2006.881959","volume":"15","author":"H R Sheikh","year":"2006","unstructured":"Sheikh H R, Sabir M F, Bovik A C. A statistical evaluation of recent full reference image quality assessment algorithms. IEEE Trans Image Process, 2006, 15: 3440\u20133451","journal-title":"IEEE Trans Image Process"}],"container-title":["Science China Information Sciences"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11432-025-4631-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11432-025-4631-2","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11432-025-4631-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,1,21]],"date-time":"2026-01-21T11:03:49Z","timestamp":1768993429000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11432-025-4631-2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,1,12]]},"references-count":112,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2026,2]]}},"alternative-id":["4631"],"URL":"https:\/\/doi.org\/10.1007\/s11432-025-4631-2","relation":{},"ISSN":["1674-733X","1869-1919"],"issn-type":[{"value":"1674-733X","type":"print"},{"value":"1869-1919","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,1,12]]},"assertion":[{"value":"28 March 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"21 July 2025","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"16 October 2025","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"12 January 2026","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}],"article-number":"122306"}}