{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,15]],"date-time":"2026-06-15T15:57:55Z","timestamp":1781539075053,"version":"3.54.5"},"publisher-location":"New York, NY, USA","reference-count":43,"publisher":"ACM","license":[{"start":{"date-parts":[[2026,6,15]],"date-time":"2026-06-15T00:00:00Z","timestamp":1781481600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/legalcode"}],"funder":[{"name":"Beijing Natural Science Foundation","award":["4254066"],"award-info":[{"award-number":["4254066"]}]},{"name":"2025 Capacity Building for Scientific and Technological Innovation Services in Universities - Fundamental Research Funds for Municipal Universities","award":["312000546325001"],"award-info":[{"award-number":["312000546325001"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2026,6,16]]},"DOI":"10.1145\/3805622.3810844","type":"proceedings-article","created":{"date-parts":[[2026,6,15]],"date-time":"2026-06-15T14:42:57Z","timestamp":1781534577000},"page":"1635-1643","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["HSS-Net: Hybrid State Space Modeling for Efficient Unified Adverse Weather Restoration"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0009-0002-5258-9438","authenticated-orcid":false,"given":"Yueqi","family":"Zhu","sequence":"first","affiliation":[{"name":"College of Computer Science, Beijing University of Technology, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0035-2391","authenticated-orcid":false,"given":"Baiwen","family":"Zhang","sequence":"additional","affiliation":[{"name":"Institute of Information and Artificial Intelligence Technology, Beijing Academy of Science and Technology, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-5876-1448","authenticated-orcid":false,"given":"Guo","family":"Cheng","sequence":"additional","affiliation":[{"name":"College of Computer Science, Beijing University of Technology, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-8260-503X","authenticated-orcid":false,"given":"Yongkang","family":"Zhang","sequence":"additional","affiliation":[{"name":"College\u00a0of\u00a0Mechanical\u00a0and\u00a0Energy\u00a0Engineering, Beijing University of Technology, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-7541-4193","authenticated-orcid":false,"given":"Feiran","family":"Liu","sequence":"additional","affiliation":[{"name":"College of Computer Science, Beijing University of Technology, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-4704-0389","authenticated-orcid":false,"given":"Er","family":"Cao","sequence":"additional","affiliation":[{"name":"College of Computer Science, Beijing University of Technology, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3634-0547","authenticated-orcid":false,"given":"Meng","family":"Xu","sequence":"additional","affiliation":[{"name":"College of Computer Science, Beijing University of Technology, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2026,6,15]]},"reference":[{"key":"e_1_3_3_1_2_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-20071-7_2"},{"key":"e_1_3_3_1_3_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58589-1_45"},{"key":"e_1_3_3_1_4_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01713"},{"key":"e_1_3_3_1_5_2","first-page":"11275","volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","author":"Chen Xiang","year":"2023","unstructured":"Xiang Chen, Hao Pan, and Jinshan Li. 2023. Drsformer: A sparse transformer for deraining. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, New York, NY, USA, 11275\u201311284."},{"key":"e_1_3_3_1_6_2","doi-asserted-by":"crossref","unstructured":"De Cheng Yanling Ji Dong Gong Yan Li Nannan Wang Junwei Han and Dingwen Zhang. 2024. Continual all-in-one adverse weather removal with knowledge replay on a unified network structure. IEEE Transactions on Multimedia 26 (2024) 8184\u20138196.","DOI":"10.1109\/TMM.2024.3377136"},{"key":"e_1_3_3_1_7_2","unstructured":"Mauricio Delbracio and Peyman Milanfar. 2023. Inversion by direct iteration: An alternative to denoising diffusion for image restoration. arXiv:2303.11435."},{"key":"e_1_3_3_1_8_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52733.2024.02385"},{"key":"e_1_3_3_1_9_2","first-page":"1","volume-title":"First conference on language modeling","author":"Gu Albert","year":"2024","unstructured":"Albert Gu and Tri Dao. 2024. Mamba: Linear-time sequence modeling with selective state spaces. In First conference on language modeling. PMLR, Brookline, MA, USA, 1\u201334."},{"key":"e_1_3_3_1_10_2","unstructured":"Albert Gu Karan Goel and Christopher R\u00e9. 2021. Efficiently modeling long sequences with structured state spaces. arXiv:2111.00396."},{"key":"e_1_3_3_1_11_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52734.2025.02619"},{"key":"e_1_3_3_1_12_2","first-page":"1","volume-title":"European Conference on Computer Vision (ECCV)","author":"Guo Hang","year":"2024","unstructured":"Hang Guo, Jinmin Li, Tao Dai, et\u00a0al. 2024. Mambair: A simple baseline for image restoration with state-space model. In European Conference on Computer Vision (ECCV). Springer, Cham, Switzerland, 1\u201318."},{"key":"e_1_3_3_1_13_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52734.2025.02352"},{"key":"e_1_3_3_1_14_2","doi-asserted-by":"crossref","unstructured":"Kaiming He Jian Sun and Xiaoou Tang. 2010. Single image haze removal using dark channel prior. IEEE transactions on pattern analysis and machine intelligence 33 12 (2010) 2341\u20132353.","DOI":"10.1109\/TPAMI.2010.168"},{"key":"e_1_3_3_1_15_2","doi-asserted-by":"crossref","unstructured":"Ashutosh Kulkarni Prashant\u00a0W Patil Subrahmanyam Murala and Sunil Gupta. 2022. Unified multi-weather visibility restoration. IEEE Transactions on Multimedia 25 (2022) 7686\u20137698.","DOI":"10.1109\/TMM.2022.3225712"},{"key":"e_1_3_3_1_16_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01693"},{"key":"e_1_3_3_1_17_2","doi-asserted-by":"crossref","unstructured":"Boyi Li Wenqi Ren Dengpan Fu Dacheng Tao Dan Feng Wenjun Zeng and Zhangyang Wang. 2018. Benchmarking single-image dehazing and beyond. IEEE Transactions on Image Processing (TIP) 28 1 (2018) 492\u2013505.","DOI":"10.1109\/TIP.2018.2867951"},{"key":"e_1_3_3_1_18_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00173"},{"key":"e_1_3_3_1_19_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00324"},{"key":"e_1_3_3_1_20_2","doi-asserted-by":"crossref","unstructured":"Xiang Li and Jianwu Li. 2025. All-in-one weather removal via Multi-Depth Gated Transformer with gradient modulation. Pattern Recognition 165 (2025) 111643.","DOI":"10.1016\/j.patcog.2025.111643"},{"key":"e_1_3_3_1_21_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52733.2024.00268"},{"key":"e_1_3_3_1_22_2","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v38i4.28164"},{"key":"e_1_3_3_1_23_2","doi-asserted-by":"crossref","unstructured":"Yue Liu Yunjie Tian Yuzhong Zhao Hongtian Yu Lingxi Xie Yaowei Wang Qixiang Ye Jianbin Jiao and Yunfan Liu. 2024. Vmamba: Visual state space model. Advances in neural information processing systems 37 (2024) 103031\u2013103063.","DOI":"10.52202\/079017-3273"},{"key":"e_1_3_3_1_24_2","doi-asserted-by":"crossref","unstructured":"Yun-Fu Liu Da-Wei Jaw Shih-Chia Huang and Jenq-Neng Hwang. 2018. DesnowNet: Context-aware deep network for snow removal. IEEE Transactions on Image Processing (TIP) 27 6 (2018) 3064\u20133073.","DOI":"10.1109\/TIP.2018.2806202"},{"key":"e_1_3_3_1_25_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52734.2025.02618"},{"key":"e_1_3_3_1_26_2","unstructured":"Simian Luo Yiqin Tan Longbo Patil et\u00a0al. 2023. Latent consistency models: Synthesizing high-resolution images with few-step inference. arXiv:2310.04378."},{"key":"e_1_3_3_1_27_2","unstructured":"Jun Ma Feifei Li and Bo Wang. 2024. U-mamba: Enhancing long-range dependency for biomedical image segmentation. arXiv:2401.04722."},{"key":"e_1_3_3_1_28_2","doi-asserted-by":"crossref","unstructured":"Srinivasa\u00a0G Narasimhan and Shree\u00a0K Nayar. 2002. Vision and the atmosphere. International journal of computer vision 48 3 (2002) 233\u2013254.","DOI":"10.1023\/A:1016328200723"},{"key":"e_1_3_3_1_29_2","doi-asserted-by":"crossref","unstructured":"Ozan \u00d6zdenizci and Robert Legenstein. 2023. Restoring vision in adverse weather conditions with patch-based denoising diffusion models. IEEE transactions on pattern analysis and machine intelligence 45 8 (2023) 10346\u201310357.","DOI":"10.1109\/TPAMI.2023.3238179"},{"key":"e_1_3_3_1_30_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV51070.2023.01983"},{"key":"e_1_3_3_1_31_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00263"},{"key":"e_1_3_3_1_32_2","doi-asserted-by":"crossref","unstructured":"Tim Salimans Thomas Mensink Jonathan Heek and Emiel Hoogeboom. 2024. Multistep distillation of diffusion models via moment matching. Advances in Neural Information Processing Systems 37 (2024) 36046\u201336070.","DOI":"10.52202\/079017-1136"},{"key":"e_1_3_3_1_33_2","doi-asserted-by":"crossref","unstructured":"Zhenning Shi Haoshuai Zheng Chen Xu Changsheng Dong Bin Pan Xueshuo Xie Along He Tao Li and Huazhu Fu. 2024. Resfusion: Denoising diffusion probabilistic models for image restoration based on prior residual noise. Advances in Neural Information Processing Systems 37 (2024) 130664\u2013130693.","DOI":"10.52202\/079017-4153"},{"key":"e_1_3_3_1_34_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00239"},{"key":"e_1_3_3_1_35_2","doi-asserted-by":"crossref","unstructured":"Jie Xiao Xueyang Fu Aiping Liu Feng Wu and Zheng-Jun Zha. 2022. Image de-raining transformer. IEEE transactions on pattern analysis and machine intelligence 45 11 (2022) 12978\u201312995.","DOI":"10.1109\/TPAMI.2022.3183612"},{"key":"e_1_3_3_1_36_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.183"},{"key":"e_1_3_3_1_37_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV51070.2023.01163"},{"key":"e_1_3_3_1_38_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00564"},{"key":"e_1_3_3_1_39_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01458"},{"key":"e_1_3_3_1_40_2","doi-asserted-by":"crossref","unstructured":"Kaihao Zhang Rongqing Li Yanjiang Yu Wenhan Luo and Changsheng Li. 2021. Deep dense multi-scale network for snow removal using semantic and depth priors. IEEE Transactions on Image Processing 30 (2021) 7419\u20137431.","DOI":"10.1109\/TIP.2021.3104166"},{"key":"e_1_3_3_1_41_2","first-page":"16812","volume-title":"Proceedings of the AAAI Conference on Artificial Intelligence","volume":"38","author":"Zhang Rongyu","year":"2024","unstructured":"Rongyu Zhang, Yulin Luo, Jiaming Liu, Huanrui Yang, Zhen Dong, Denis Gudovskiy, Tomoyuki Okuno, Yohei Nakata, Kurt Keutzer, Yuan Du, et\u00a0al. 2024. Efficient deweather mixture-of-experts with uncertainty-aware feature-wise linear modulation. In Proceedings of the AAAI Conference on Artificial Intelligence , Vol.\u00a038. AAAI Press, Washington, DC, USA, 16812\u201316820."},{"key":"e_1_3_3_1_42_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52734.2025.01388"},{"key":"e_1_3_3_1_43_2","first-page":"61816","volume-title":"International Conference on Machine Learning (ICML)","author":"Zhu Lianghui","year":"2024","unstructured":"Lianghui Zhu, Bencheng Liao, Qian Zhang, Xinwen Wang, Wenyu Liu, and Xinggang Wang. 2024. Vision mamba: Efficient visual representation learning with bidirectional state space model. In International Conference on Machine Learning (ICML). PMLR, Brookline, MA, USA, 61816\u201361835."},{"key":"e_1_3_3_1_44_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.02083"}],"event":{"name":"ICMR '26: International Conference on Multimedia Retrieval","location":"Amsterdam The Netherlands","acronym":"ICMR '26","sponsor":["SIGMM ACM Special Interest Group on Multimedia"]},"container-title":["Proceedings of the 2026 International Conference on Multimedia Retrieval"],"original-title":[],"deposited":{"date-parts":[[2026,6,15]],"date-time":"2026-06-15T15:50:13Z","timestamp":1781538613000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3805622.3810844"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,6,15]]},"references-count":43,"alternative-id":["10.1145\/3805622.3810844","10.1145\/3805622"],"URL":"https:\/\/doi.org\/10.1145\/3805622.3810844","relation":{},"subject":[],"published":{"date-parts":[[2026,6,15]]},"assertion":[{"value":"2026-06-15","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}