{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,3]],"date-time":"2026-06-03T11:07:26Z","timestamp":1780484846720,"version":"3.54.1"},"reference-count":84,"publisher":"Springer Science and Business Media LLC","issue":"5","license":[{"start":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T00:00:00Z","timestamp":1777420800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T00:00:00Z","timestamp":1777420800000},"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":["Int J Comput Vis"],"published-print":{"date-parts":[[2026,5]]},"DOI":"10.1007\/s11263-026-02829-9","type":"journal-article","created":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T02:59:26Z","timestamp":1777431566000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Scene Prior Filtering for Depth Super-Resolution"],"prefix":"10.1007","volume":"134","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4668-2559","authenticated-orcid":false,"given":"Zhengxue","family":"Wang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhiqiang","family":"Yan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ming-Hsuan","family":"Yang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jinshan","family":"Pan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Guangwei","family":"Gao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ying","family":"Tai","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jian","family":"Yang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,4,29]]},"reference":[{"issue":"10","key":"2829_CR1","doi-asserted-by":"publisher","first-page":"3012","DOI":"10.1109\/TGRS.2007.904923","volume":"45","author":"L Alparone","year":"2007","unstructured":"Alparone, L., Wald, L., Chanussot, J., Thomas, C., Gamba, P., & Bruce, L. M. (2007). Comparison of pansharpening algorithms: Outcome of the 2006 grs-s data-fusion contest. IEEE Transactions on Geoscience and Remote Sensing, 45(10), 3012\u20133021.","journal-title":"IEEE Transactions on Geoscience and Remote Sensing"},{"issue":"6","key":"2829_CR2","doi-asserted-by":"publisher","first-page":"5206","DOI":"10.1109\/TGRS.2020.3015878","volume":"59","author":"J Cai","year":"2020","unstructured":"Cai, J., & Huang, B. (2020). Super-resolution-guided progressive pansharpening based on a deep convolutional neural network. IEEE Transactions on Geoscience and Remote Sensing, 59(6), 5206\u20135220.","journal-title":"IEEE Transactions on Geoscience and Remote Sensing"},{"key":"2829_CR3","doi-asserted-by":"crossref","unstructured":"Cheng, X., Wang, P.& Yang, R. (2018) Learning depth with convolutional spatial propagation network. In: Proceedings of the European Conference on Computer Vision, 103\u2013119","DOI":"10.1007\/978-3-030-01270-0_7"},{"key":"2829_CR4","doi-asserted-by":"crossref","unstructured":"De Lutio, R., Becker, A., D\u2019Aronco, S., Russo, S., Wegner, J.D. & Schindler, K. (2022) Learning graph regularisation for guided super-resolution. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 1979\u20131988","DOI":"10.1109\/CVPR52688.2022.00202"},{"issue":"10","key":"2829_CR5","doi-asserted-by":"publisher","first-page":"3333","DOI":"10.1109\/TPAMI.2020.2984244","volume":"43","author":"X Deng","year":"2020","unstructured":"Deng, X., & Dragotti, P. L. (2020). Deep convolutional neural network for multi-modal image restoration and fusion. IEEE Transactions on Pattern Analysis and Machine Intelligence, 43(10), 3333\u20133348.","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"issue":"5","key":"2829_CR6","doi-asserted-by":"publisher","first-page":"2770","DOI":"10.1109\/TPAMI.2023.3334624","volume":"46","author":"X Deng","year":"2023","unstructured":"Deng, X., Xu, J., Gao, F., Sun, X., & Xu, M. (2023). Deepm 2 cdl: Deep multi-scale multi-modal convolutional dictionary learning network. IEEE Transactions on Pattern Analysis and Machine Intelligence, 46(5), 2770\u20132787.","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"key":"2829_CR7","doi-asserted-by":"crossref","unstructured":"Dong, X., Yokoya, N., Wang, L. & Uezato, T. (2022) Learning mutual modulation for self-supervised cross-modal super-resolution. In: Proceedings of the European Conference on Computer Vision, 1\u201318. Springer","DOI":"10.1007\/978-3-031-19800-7_1"},{"key":"2829_CR8","doi-asserted-by":"crossref","unstructured":"Eftekhar, A., Sax, A., Malik, J. & Zamir, A. (2021) Omnidata: A scalable pipeline for making multi-task mid-level vision datasets from 3d scans. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, 10786\u201310796","DOI":"10.1109\/ICCV48922.2021.01061"},{"key":"2829_CR9","doi-asserted-by":"crossref","unstructured":"Fan, R., Wang, H., Cai, P. & Liu, M. (2020) Sne-roadseg: Incorporating surface normal information into semantic segmentation for accurate freespace detection. In: Proceedings of the European Conference on Computer Vision, 340\u2013356. Springer","DOI":"10.1007\/978-3-030-58577-8_21"},{"key":"2829_CR10","doi-asserted-by":"crossref","unstructured":"Gu, S., Zuo, W., Guo, S., Chen, Y., Chen, C.& Zhang, L. (2017) Learning dynamic guidance for depth image enhancement. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 3769\u20133778","DOI":"10.1109\/CVPR.2017.83"},{"issue":"5","key":"2829_CR11","doi-asserted-by":"publisher","first-page":"2545","DOI":"10.1109\/TIP.2018.2887029","volume":"28","author":"C Guo","year":"2018","unstructured":"Guo, C., Li, C., Guo, J., Cong, R., Fu, H., & Han, P. (2018). Hierarchical features driven residual learning for depth map super-resolution. IEEE Transactions on Image Processing, 28(5), 2545\u20132557.","journal-title":"IEEE Transactions on Image Processing"},{"issue":"6","key":"2829_CR12","doi-asserted-by":"publisher","first-page":"1397","DOI":"10.1109\/TPAMI.2012.213","volume":"35","author":"K He","year":"2012","unstructured":"He, K., Sun, J., & Tang, X. (2012). Guided image filtering. IEEE Transactions on Pattern Analysis and Machine Intelligence, 35(6), 1397\u20131409.","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"key":"2829_CR13","doi-asserted-by":"crossref","unstructured":"He, L., Zhu, H., Li, F., Bai, H., Cong, R., Zhang, C., Lin, C., Liu, M. & Zhao, Y. (2021) Towards fast and accurate real-world depth super-resolution: Benchmark dataset and baseline. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 9229\u20139238","DOI":"10.1109\/CVPR46437.2021.00911"},{"key":"2829_CR14","doi-asserted-by":"crossref","unstructured":"Hirschmuller, H. & Scharstein, D. (2007) Evaluation of cost functions for stereo matching. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 1\u20138. IEEE","DOI":"10.1109\/CVPR.2007.383248"},{"issue":"12","key":"2829_CR15","doi-asserted-by":"publisher","first-page":"10579","DOI":"10.1109\/TPAMI.2024.3444912","volume":"46","author":"M Hu","year":"2024","unstructured":"Hu, M., Yin, W., Zhang, C., Cai, Z., Long, X., Chen, H., Wang, K., Yu, G., Shen, C., & Shen, S. (2024). Metric3d v2: A versatile monocular geometric foundation model for zero-shot metric depth and surface normal estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 46(12), 10579\u201310596.","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"key":"2829_CR16","doi-asserted-by":"crossref","unstructured":"Jiang, K., Jiang, J., Wang, Z., Geng, Z. & Liu, X. (2025) Dawn+: Wavelet-based image deraining meets direction-aware attention and mutual representation. IEEE Transactions on Neural Networks and Learning Systems","DOI":"10.1109\/TNNLS.2025.3587248"},{"key":"2829_CR17","doi-asserted-by":"crossref","unstructured":"Jung, H., Park, E. & Yoo, S. (2021) Fine-grained semantics-aware representation enhancement for self-supervised monocular depth estimation. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, 12642\u201312652","DOI":"10.1109\/ICCV48922.2021.01241"},{"issue":"2","key":"2829_CR18","doi-asserted-by":"publisher","first-page":"579","DOI":"10.1007\/s11263-020-01386-z","volume":"129","author":"B Kim","year":"2021","unstructured":"Kim, B., Ponce, J., & Ham, B. (2021). Deformable kernel networks for joint image filtering. International Journal of Computer Vision, 129(2), 579\u2013600.","journal-title":"International Journal of Computer Vision"},{"key":"2829_CR19","unstructured":"Kingma, D.P. & Ba, J. (2014) Adam: A method for stochastic optimization. arXiv:1412.6980"},{"key":"2829_CR20","doi-asserted-by":"crossref","unstructured":"Kirillov, A., Mintun, E., Ravi, N., Mao, H., Rolland, C., Gustafson, L., Xiao, T., Whitehead, S., Berg, A.C., Lo, W.Y., et al. (2023) Segment anything. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, 4015\u20134026","DOI":"10.1109\/ICCV51070.2023.00371"},{"issue":"3","key":"2829_CR21","doi-asserted-by":"publisher","first-page":"689","DOI":"10.1145\/1015706.1015780","volume":"23","author":"A Levin","year":"2004","unstructured":"Levin, A., Lischinski, D., & Weiss, Y. (2004). Colorization using optimization. ACM Transactions on Graphics, 23(3), 689\u2013694.","journal-title":"ACM Transactions on Graphics"},{"key":"2829_CR22","doi-asserted-by":"crossref","unstructured":"Li, Y., Huang, J.B., Ahuja, N.& Yang, M.H. (2016) Deep joint image filtering. In: Proceedings of the European Conference on Computer Vision, 154\u2013169. Springer","DOI":"10.1007\/978-3-319-46493-0_10"},{"issue":"8","key":"2829_CR23","doi-asserted-by":"publisher","first-page":"1909","DOI":"10.1109\/TPAMI.2018.2890623","volume":"41","author":"Y Li","year":"2019","unstructured":"Li, Y., Huang, J. B., Ahuja, N., & Yang, M. H. (2019). Joint image filtering with deep convolutional networks. IEEE Transactions on Pattern Analysis and Machine Intelligence, 41(8), 1909\u20131923.","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"key":"2829_CR24","doi-asserted-by":"crossref","unstructured":"Li, Y., Yang, X., Fu, J., Yue, G. & Zhou, W. (2024) Deep bi-directional attention network for image super-resolution quality assessment. In: Proceedings of the IEEE International Conference on Multimedia and Expo (ICME), 1\u20136. IEEE","DOI":"10.1109\/ICME57554.2024.10687430"},{"key":"2829_CR25","doi-asserted-by":"publisher","first-page":"7728","DOI":"10.1109\/TIP.2025.3633145","volume":"34","author":"Y Li","year":"2025","unstructured":"Li, Y., Yang, X., Yue, G., Fu, J., Jiang, Q., Jia, X., Rosin, P. L., Liu, H., & Zhou, W. (2025). Perception-oriented bidirectional attention network for image super-resolution quality assessment. IEEE Transactions on Image Processing, 34, 7728\u20137743.","journal-title":"IEEE Transactions on Image Processing"},{"key":"2829_CR26","doi-asserted-by":"crossref","unstructured":"Liao, W., Huang, X., Van Coillie, F., Thoonen, G., Pi\u017eurica, A., Scheunders, P. & Philips, W. (2015) Two-stage fusion of thermal hyperspectral and visible rgb image by pca and guided filter. In: Proceedings of Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, 1\u20134","DOI":"10.1109\/WHISPERS.2015.8075405"},{"key":"2829_CR27","doi-asserted-by":"crossref","unstructured":"Lu, S., Ren, X. & Liu, F. (2014) Depth enhancement via low-rank matrix completion. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 3390\u20133397","DOI":"10.1109\/CVPR.2014.433"},{"key":"2829_CR28","doi-asserted-by":"crossref","unstructured":"Metzger, N., Daudt, R.C. & Schindler, K. (2023) Guided depth super-resolution by deep anisotropic diffusion. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 18237\u201318246","DOI":"10.1109\/CVPR52729.2023.01749"},{"key":"2829_CR29","doi-asserted-by":"crossref","unstructured":"Pan, J., Dong, J., Ren, J.S., Lin, L., Tang, J. & Yang, M.H. (2019) Spatially variant linear representation models for joint filtering. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 1702\u20131711","DOI":"10.1109\/CVPR.2019.00180"},{"key":"2829_CR30","doi-asserted-by":"crossref","unstructured":"Park, J., Joo, K., Hu, Z., Liu, C.K. & So Kweon, I. (2020) Non-local spatial propagation network for depth completion. In: Proceedings of the European Conference on Computer Vision, 120\u2013136. Springer","DOI":"10.1007\/978-3-030-58601-0_8"},{"issue":"11","key":"2829_CR31","doi-asserted-by":"publisher","first-page":"4954","DOI":"10.1007\/s11263-024-02089-5","volume":"132","author":"X Qiao","year":"2024","unstructured":"Qiao, X., Poggi, M., Deng, P., Wei, H., Ge, C., & Mattoccia, S. (2024). Rgb guided tof imaging system: A survey of deep learning-based methods. International Journal of Computer Vision, 132(11), 4954\u20134991.","journal-title":"International Journal of Computer Vision"},{"key":"2829_CR32","doi-asserted-by":"crossref","unstructured":"Qiu, J., Cui, Z., Zhang, Y., Zhang, X., Liu, S., Zeng, B. & Pollefeys, M. (2019) Deeplidar: Deep surface normal guided depth prediction for outdoor scene from sparse lidar data and single color image. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 3313\u20133322","DOI":"10.1109\/CVPR.2019.00343"},{"key":"2829_CR33","doi-asserted-by":"crossref","unstructured":"Scharstein, D. & Pal, C. (2007) Learning conditional random fields for stereo. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 1\u20138","DOI":"10.1109\/CVPR.2007.383191"},{"issue":"12","key":"2829_CR34","doi-asserted-by":"publisher","first-page":"8883","DOI":"10.1109\/TPAMI.2024.3411571","volume":"46","author":"S Shao","year":"2024","unstructured":"Shao, S., Pei, Z., Chen, W., Chen, P. C., & Li, Z. (2024). Nddepth: Normal-distance assisted monocular depth estimation and completion. IEEE Transactions on Pattern Analysis and Machine Intelligence, 46(12), 8883\u20138899.","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"key":"2829_CR35","doi-asserted-by":"crossref","unstructured":"Shen, X., Zhou, C., Xu, L. & Jia, J. (2015) Mutual-structure for joint filtering. In: Proceedings of the IEEE\/CVF international conference on computer vision, 3406\u20133414","DOI":"10.1109\/ICCV.2015.389"},{"key":"2829_CR36","doi-asserted-by":"crossref","unstructured":"Shi, W., Ye, M. & Du, B. (2022) Symmetric uncertainty-aware feature transmission for depth super-resolution. In: Proceedings of the ACM International Conference on Multimedia, 3867\u20133876","DOI":"10.1145\/3503161.3547873"},{"key":"2829_CR37","doi-asserted-by":"crossref","unstructured":"Shin, J., Shin, S. & Jeon, H.G. (2023) Task-specific scene structure representations. In: Proceedings of the AAAI Conference on Artificial Intelligence, 2272\u20132281","DOI":"10.1609\/aaai.v37i2.25322"},{"key":"2829_CR38","doi-asserted-by":"crossref","unstructured":"Silberman, N., Hoiem, D., Kohli, P. & Fergus, R. (2012) Indoor segmentation and support inference from rgbd images. In: Proceedings of the European Conference on Computer Vision, 746\u2013760. Springer","DOI":"10.1007\/978-3-642-33715-4_54"},{"key":"2829_CR39","doi-asserted-by":"crossref","unstructured":"Song, X., Dai, Y., Zhou, D., Liu, L., Li, W., Li, H. & Yang, R. (2020) Channel attention based iterative residual learning for depth map super-resolution. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 5631\u20135640","DOI":"10.1109\/CVPR42600.2020.00567"},{"key":"2829_CR40","doi-asserted-by":"crossref","unstructured":"Su, H., Jampani, V., Sun, D., Gallo, O., Learned-Miller, E. & Kautz, J. (2019) Pixel-adaptive convolutional neural networks. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 11166\u201311175","DOI":"10.1109\/CVPR.2019.01142"},{"key":"2829_CR41","doi-asserted-by":"crossref","unstructured":"Sun, B., Ye, X., Li, B., Li, H., Wang, Z. & Xu, R. (2021) Learning scene structure guidance via cross-task knowledge transfer for single depth super-resolution. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 7792\u20137801","DOI":"10.1109\/CVPR46437.2021.00770"},{"key":"2829_CR42","doi-asserted-by":"publisher","first-page":"1116","DOI":"10.1109\/TIP.2020.3040528","volume":"30","author":"J Tang","year":"2020","unstructured":"Tang, J., Tian, F. P., Feng, W., Li, J., & Tan, P. (2020). Learning guided convolutional network for depth completion. IEEE Transactions on Image Processing, 30, 1116\u20131129.","journal-title":"IEEE Transactions on Image Processing"},{"key":"2829_CR43","doi-asserted-by":"crossref","unstructured":"Van Gansbeke, W., Neven, D., De Brabandere, B. & Van Gool, L. (2019) Sparse and noisy lidar completion with rgb guidance and uncertainty. In: Proceedings of the International Conference on Machine Vision Applications, 1\u20136. IEEE","DOI":"10.23919\/MVA.2019.8757939"},{"key":"2829_CR44","doi-asserted-by":"crossref","unstructured":"Viola, M., Qu, K., Metzger, N., Ke, B., Becker, A., Schindler, K. & Obukhov, A. (2025) Marigold-dc: Zero-shot monocular depth completion with guided diffusion. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, 5359\u20135370","DOI":"10.1109\/ICCV51701.2025.00509"},{"issue":"6","key":"2829_CR45","first-page":"691","volume":"63","author":"L Wald","year":"1997","unstructured":"Wald, L., Ranchin, T., & Mangolini, M. (1997). Fusion of satellite images of different spatial resolutions: Assessing the quality of resulting images. Photogrammetric Engineering and Remote Sensing, 63(6), 691\u2013699.","journal-title":"Photogrammetric Engineering and Remote Sensing"},{"key":"2829_CR46","doi-asserted-by":"crossref","unstructured":"Wang, J., Chen, M., Karaev, N., Vedaldi, A., Rupprecht, C. & Novotny, D. (2025) Vggt: Visual geometry grounded transformer. In: Proceedings of the Computer Vision and Pattern Recognition Conference, 5294\u20135306","DOI":"10.1109\/CVPR52734.2025.00499"},{"key":"2829_CR47","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2022.109260","volume":"136","author":"K Wang","year":"2023","unstructured":"Wang, K., Zhao, L., Zhang, J., Zhang, J., Wang, A., & Bai, H. (2023). Joint depth map super-resolution method via deep hybrid-cross guidance filter. Pattern Recognition, 136, Article 109260.","journal-title":"Pattern Recognition"},{"key":"2829_CR48","unstructured":"Wang, Z., Chen, S., Yang, L., Wang, J., Zhang, Z., Zhao, H. & Zhao, Z. (2025) Depth anything with any prior. arXiv:2505.10565"},{"key":"2829_CR49","unstructured":"Wang, Z., Wu, Y., Li, X., Yan, Z. & Yang, J. (2025) Spatiotemporal difference network for video depth super-resolution. arXiv:2508.01259"},{"key":"2829_CR50","doi-asserted-by":"crossref","unstructured":"Wang, Z., Yan, Z., Pan, J., Gao, G., Zhang, K.& Yang, J. (2025) Dornet: A degradation oriented and regularized network for blind depth super-resolution. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 15813\u201315822","DOI":"10.1109\/CVPR52734.2025.01474"},{"key":"2829_CR51","unstructured":"Wang, Z., Yan, Z., Wu, Y., Gao, G., Li, X. & Yang, J. (2025) Multi-order matching network for alignment-free depth super-resolution. arXiv:2511.16361"},{"key":"2829_CR52","doi-asserted-by":"crossref","unstructured":"Wang, Z., Yan, Z. & Yang, J. (2024) Sgnet: Structure guided network via gradient-frequency awareness for depth map super-resolution. In: Proceedings of the AAAI Conference on Artificial Intelligence, 5823\u20135831","DOI":"10.1609\/aaai.v38i6.28395"},{"key":"2829_CR53","doi-asserted-by":"crossref","unstructured":"Wu, Y., Pan, C., Wang, G., Yang, Y., Wei, J., Li, C. & Shen, H.T. (2023) Learning semantic-aware knowledge guidance for low-light image enhancement. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 1662\u20131671","DOI":"10.1109\/CVPR52729.2023.00166"},{"key":"2829_CR54","unstructured":"Xiao, Y., Yuan, Q., Jiang, K., Huang, W., Zhang, Q., Zheng, T., Lin, C.W. & Zhang, L. (2025) Spiking meets attention: Efficient remote sensing image super-resolution with attention spiking neural networks. arXiv:2503.04223"},{"key":"2829_CR55","doi-asserted-by":"crossref","unstructured":"Xu, S., Zhang, J., Zhao, Z., Sun, K., Liu, J. & Zhang, C. (2021) Deep gradient projection networks for pan-sharpening. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 1366\u20131375","DOI":"10.1109\/CVPR46437.2021.00142"},{"key":"2829_CR56","doi-asserted-by":"crossref","unstructured":"Xu, Y., Zhu, X., Shi, J., Zhang, G., Bao, H.& Li, H. (2019) Depth completion from sparse lidar data with depth-normal constraints. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, 2811\u20132820","DOI":"10.1109\/ICCV.2019.00290"},{"key":"2829_CR57","unstructured":"Yan, Z., Li, X., Wang, K., Chen, S., Li, J. & Yang, J. (2023) Distortion and uncertainty aware loss for panoramic depth completion. In: Proceedings of the International Conference on Machine Learning, 39099\u201339109. PMLR"},{"key":"2829_CR58","doi-asserted-by":"crossref","unstructured":"Yan, Z., Lin, Y., Wang, K., Zheng, Y., Wang, Y., Zhang, Z., Li, J. & Yang, J. (2024) Tri-perspective view decomposition for geometry-aware depth completion. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 4874\u20134884","DOI":"10.1109\/CVPR52733.2024.00466"},{"key":"2829_CR59","doi-asserted-by":"crossref","unstructured":"Yan, Z., Wang, K., Li, X., Gao, G., Li, J. & Yang, J. (2025) Tri-perspective view decomposition for geometry aware depth completion and super-resolution. IEEE Transactions on Pattern Analysis and Machine Intelligence","DOI":"10.1109\/TPAMI.2025.3596391"},{"issue":"4","key":"2829_CR60","doi-asserted-by":"publisher","first-page":"5616","DOI":"10.1109\/TNNLS.2022.3208330","volume":"35","author":"Z Yan","year":"2022","unstructured":"Yan, Z., Wang, K., Li, X., Zhang, Z., Li, G., Li, J., & Yang, J. (2022). Learning complementary correlations for depth super-resolution with incomplete data in real world. IEEE Transactions on Neural Networks and Learning Systems, 35(4), 5616\u20135626.","journal-title":"IEEE Transactions on Neural Networks and Learning Systems"},{"key":"2829_CR61","doi-asserted-by":"crossref","unstructured":"Yan, Z., Wang, K., Li, X., Zhang, Z., Li, J. & Yang, J. (2022) Rignet: Repetitive image guided network for depth completion. In: Proceedings of the European Conference on Computer Vision, 214\u2013230. Springer","DOI":"10.1007\/978-3-031-19812-0_13"},{"key":"2829_CR62","doi-asserted-by":"crossref","unstructured":"Yan, Z., Wang, K., Li, X., Zhang, Z., Li, J. & Yang, J. (2023) Desnet: Decomposed scale-consistent network for unsupervised depth completion. In: Proceedings of the AAAI Conference on Artificial Intelligence, 3109\u20133117","DOI":"10.1609\/aaai.v37i3.25415"},{"key":"2829_CR63","doi-asserted-by":"crossref","unstructured":"Yan, Z., Wang, Z., Dong, H., Li, J., Yang, J. & Lee, G.H. (2025) Ducos: Duality constrained depth super-resolution via foundation model. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, 8361\u20138371","DOI":"10.1109\/ICCV51701.2025.00783"},{"key":"2829_CR64","doi-asserted-by":"crossref","unstructured":"Yang, C., Zhang, L., Lu, H., Ruan, X. & Yang, M.H. (2013) Saliency detection via graph-based manifold ranking. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 3166\u20133173","DOI":"10.1109\/CVPR.2013.407"},{"key":"2829_CR65","doi-asserted-by":"crossref","unstructured":"Yang, G., Cao, X., Xiao, W., Zhou, M., Liu, A., Chen, X. & Meng, D. (2023) Panflownet: A flow-based deep network for pan-sharpening. In: Proceedings of the IEEE\/CVF international conference on computer vision, 16857\u201316867","DOI":"10.1109\/ICCV51070.2023.01546"},{"key":"2829_CR66","doi-asserted-by":"crossref","unstructured":"Yang, G., Zhao, H., Shi, J., Deng, Z. & Jia, J. (2018) Segstereo: Exploiting semantic information for disparity estimation. In: Proceedings of the European Conference on Computer Vision, 636\u2013651","DOI":"10.1007\/978-3-030-01234-2_39"},{"key":"2829_CR67","doi-asserted-by":"crossref","unstructured":"Yang, J., Fu, X., Hu, Y., Huang, Y., Ding, X. & Paisley, J. (2017) Pannet: A deep network architecture for pan-sharpening. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, 5449\u20135457","DOI":"10.1109\/ICCV.2017.193"},{"issue":"2","key":"2829_CR68","doi-asserted-by":"publisher","first-page":"267","DOI":"10.1007\/s11263-021-01545-w","volume":"130","author":"Y Yang","year":"2022","unstructured":"Yang, Y., Cao, Q., Zhang, J., & Tao, D. (2022). Codon: on orchestrating cross-domain attentions for depth super-resolution. International Journal of Computer Vision, 130(2), 267\u2013284.","journal-title":"International Journal of Computer Vision"},{"key":"2829_CR69","doi-asserted-by":"crossref","unstructured":"Yu, Z., Sheng, Z., Zhou, Z., Luo, L., Cao, S.Y., Gu, H., Zhang, H. & Shen, H.L. (2023) Aggregating feature point cloud for depth completion. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, 8732\u20138743","DOI":"10.1109\/ICCV51070.2023.00802"},{"key":"2829_CR70","doi-asserted-by":"crossref","unstructured":"Yuan, J., Jiang, H., Li, X., Qian, J., Li, J. & Yang, J. (2023) Recurrent structure attention guidance for depth super-resolution. In: Proceedings of the AAAI Conference on Artificial Intelligence, 3331\u20133339","DOI":"10.1609\/aaai.v37i3.25440"},{"issue":"3","key":"2829_CR71","doi-asserted-by":"publisher","first-page":"978","DOI":"10.1109\/JSTARS.2018.2794888","volume":"11","author":"Q Yuan","year":"2018","unstructured":"Yuan, Q., Wei, Y., Meng, X., Shen, H., & Zhang, L. (2018). A multiscale and multidepth convolutional neural network for remote sensing imagery pan-sharpening. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 11(3), 978\u2013989.","journal-title":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing"},{"key":"2829_CR72","unstructured":"Yuhas, R.H., Goetz, A.F. & Boardman, J.W. (1992) Discrimination among semi-arid landscape endmembers using the spectral angle mapper (sam) algorithm. In: JPL, Summaries of the Third Annual JPL Airborne Geoscience Workshop. 1: AVIRIS Workshop"},{"key":"2829_CR73","unstructured":"Zhang, C., Han, D., Qiao, Y., Kim, J.U., Bae, S.H., Lee, S. & Hong, C.S. (2023) Faster segment anything: Towards lightweight sam for mobile applications. arXiv:2306.14289"},{"key":"2829_CR74","first-page":"1","volume":"72","author":"R Zhang","year":"2023","unstructured":"Zhang, R., & Wu, J. (2023). A bidirectional guided filter used for rgb-d maps. IEEE Transactions on Instrumentation and Measurement, 72, 1\u201314.","journal-title":"IEEE Transactions on Instrumentation and Measurement"},{"key":"2829_CR75","doi-asserted-by":"crossref","unstructured":"Zhang, Y., Guo, X., Poggi, M., Zhu, Z., Huang, G. & Mattoccia, S. (2023) Completionformer: Depth completion with convolutions and vision transformers. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 18527\u201318536","DOI":"10.1109\/CVPR52729.2023.01777"},{"key":"2829_CR76","doi-asserted-by":"crossref","unstructured":"Zhang, Y., Zhou, S. & Li, H. (2024) Depth information assisted collaborative mutual promotion network for single image dehazing. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 2846\u20132855","DOI":"10.1109\/CVPR52733.2024.00275"},{"key":"2829_CR77","doi-asserted-by":"crossref","unstructured":"Zhao, Z., Zhang, J., Gu, X., Tan, C., Xu, S., Zhang, Y., Timofte, R. & Van Gool, L. (2023) Spherical space feature decomposition for guided depth map super-resolution. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, 12547\u201312558","DOI":"10.1109\/ICCV51070.2023.01153"},{"key":"2829_CR78","doi-asserted-by":"crossref","unstructured":"Zhao, Z., Zhang, J., Xu, S., Lin, Z. & Pfister, H. (2022) Discrete cosine transform network for guided depth map super-resolution. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 5697\u20135707","DOI":"10.1109\/CVPR52688.2022.00561"},{"key":"2829_CR79","doi-asserted-by":"publisher","first-page":"648","DOI":"10.1109\/TIP.2021.3131041","volume":"31","author":"Z Zhong","year":"2021","unstructured":"Zhong, Z., Liu, X., Jiang, J., Zhao, D., Chen, Z., & Ji, X. (2021). High-resolution depth maps imaging via attention-based hierarchical multi-modal fusion. IEEE Transactions on Image Processing, 31, 648\u2013663.","journal-title":"IEEE Transactions on Image Processing"},{"issue":"4","key":"2829_CR80","first-page":"12236","volume":"35","author":"Z Zhong","year":"2023","unstructured":"Zhong, Z., Liu, X., Jiang, J., Zhao, D., & Ji, X. (2023). Deep attentional guided image filtering. IEEE Transactions on Neural Networks and Learning Systems, 35(4), 12236\u201312250.","journal-title":"IEEE Transactions on Neural Networks and Learning Systems"},{"key":"2829_CR81","doi-asserted-by":"crossref","unstructured":"Zhou, M., Yan, K., Huang, J., Yang, Z., Fu, X. & Zhao, F. (2022) Mutual information-driven pan-sharpening. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 1798\u20131808","DOI":"10.1109\/CVPR52688.2022.00184"},{"issue":"1","key":"2829_CR82","doi-asserted-by":"publisher","first-page":"215","DOI":"10.1007\/s11263-022-01699-1","volume":"131","author":"M Zhou","year":"2023","unstructured":"Zhou, M., Yan, K., Pan, J., Ren, W., Xie, Q., & Cao, X. (2023). Memory-augmented deep unfolding network for guided image super-resolution. International Journal of Computer Vision, 131(1), 215\u2013242.","journal-title":"International Journal of Computer Vision"},{"key":"2829_CR83","doi-asserted-by":"crossref","unstructured":"Zhou, W., Jiang, Q., Wang, Y., Chen, Z., & Li, W. (2020). Blind quality assessment for image superresolution using deep two-stream convolutional networks. Information Sciences,528, 205\u2013218.","DOI":"10.1016\/j.ins.2020.04.030"},{"key":"2829_CR84","doi-asserted-by":"crossref","unstructured":"Zhou, W. & Wang, Z. (2022) Quality assessment of image super-resolution: Balancing deterministic and statistical fidelity. In: Proceedings of the ACM international conference on multimedia, 934\u2013942","DOI":"10.1145\/3503161.3547899"}],"updated-by":[{"DOI":"10.1007\/s11263-026-02883-3","type":"correction","label":"Correction","source":"publisher","updated":{"date-parts":[[2026,5,18]],"date-time":"2026-05-18T00:00:00Z","timestamp":1779062400000}}],"container-title":["International Journal of Computer Vision"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11263-026-02829-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11263-026-02829-9","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11263-026-02829-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,6,3]],"date-time":"2026-06-03T10:29:44Z","timestamp":1780482584000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11263-026-02829-9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,4,29]]},"references-count":84,"journal-issue":{"issue":"5","published-print":{"date-parts":[[2026,5]]}},"alternative-id":["2829"],"URL":"https:\/\/doi.org\/10.1007\/s11263-026-02829-9","relation":{},"ISSN":["0920-5691","1573-1405"],"issn-type":[{"value":"0920-5691","type":"print"},{"value":"1573-1405","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,4,29]]},"assertion":[{"value":"1 December 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"21 March 2026","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"29 April 2026","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"18 May 2026","order":5,"name":"change_date","label":"Change Date","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"Correction","order":6,"name":"change_type","label":"Change Type","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"A Correction to this paper has been published:","order":7,"name":"change_details","label":"Change Details","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"https:\/\/doi.org\/10.1007\/s11263-026-02883-3","URL":"https:\/\/doi.org\/10.1007\/s11263-026-02883-3","order":8,"name":"change_details","label":"Change Details","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare that they have no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflicts of Interest"}}],"article-number":"251"}}