{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/sosr-source-free-image-super-resolution-with","title":"Uncertainty-Aware Source-Free Adaptive Image Super-Resolution with Wavelet Augmentation Transformer","arxiv_id":"2303.17783","date":"2023-03-31","proceeding":"CVPR 2024 1","authors":["Yuang Ai","Xiaoqiang Zhou","Huaibo Huang","Lei Zhang","Ran He"],"abstract":"Unsupervised Domain Adaptation (UDA) can effectively address domain gap issues in real-world image Super-Resolution (SR) by accessing both the source and target data. Considering privacy policies or transmission restrictions of source data in practical scenarios, we propose a SOurce-free Domain Adaptation framework for image SR (SODA-SR) to address this issue, i.e., adapt a source-trained model to a target domain with only unlabeled target data. SODA-SR leverages the source-trained model to generate refined pseudo-labels for teacher-student learning. To better utilize pseudo-labels, we propose a novel wavelet-based augmentation method, named Wavelet Augmentation Transformer (WAT), which can be flexibly incorporated with existing networks, to implicitly produce useful augmented data. WAT learns low-frequency information of varying levels across diverse samples, which is aggregated efficiently via deformable attention. Furthermore, an uncertainty-aware self-training mechanism is proposed to improve the accuracy of pseudo-labels, with inaccurate predictions being rectified by uncertainty estimation. To acquire better SR results and avoid overfitting pseudo-labels, several regularization losses are proposed to constrain target LR and SR images in the frequency domain. Experiments show that without accessing source data, SODA-SR outperforms state-of-the-art UDA methods in both synthetic$\\rightarrow$real and real$\\rightarrow$real adaptation settings, and is not constrained by specific network architectures.","url_abs":"https://arxiv.org/abs/2303.17783v5","url_pdf":"https://arxiv.org/pdf/2303.17783v5.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"sosr-source-free-image-super-resolution-with","repo_url":"https://github.com/shallowdream204/SODA-SR","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok","spdx":"Apache-2.0"}}],"tasks":[{"task_slug":"domain-adaptation","task_name":"Domain Adaptation"},{"task_slug":"image-super-resolution","task_name":"Image Super-Resolution"},{"task_slug":"source-free-domain-adaptation","task_name":"Source-Free Domain Adaptation"},{"task_slug":"super-resolution","task_name":"Super-Resolution"},{"task_slug":"unsupervised-domain-adaptation","task_name":"Unsupervised Domain Adaptation"}],"methods":[{"method_slug":"absolute-position-encodings","method_name":"Absolute Position Encodings"},{"method_slug":"adam","method_name":"Adam"},{"method_slug":"attention","method_name":"Attention"},{"method_slug":"bpe","method_name":"BPE"},{"method_slug":"dense-connections","method_name":"Dense Connections"},{"method_slug":"dropout","method_name":"Dropout"},{"method_slug":"label-smoothing","method_name":"Label Smoothing"},{"method_slug":"layer-normalization","method_name":"Layer Normalization"},{"method_slug":"linear-layer","method_name":"Linear Layer"},{"method_slug":"multi-head-attention","method_name":"Multi-Head Attention"},{"method_slug":"position-wise-feed-forward-layer","method_name":"Position-Wise Feed-Forward Layer"},{"method_slug":"residual-connection","method_name":"Residual Connection"},{"method_slug":"softmax","method_name":"Softmax"},{"method_slug":"transformer","method_name":"Transformer"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":"https://app.syntology.ai/?focus=2303.17783","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2303.17783"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-24T18:15:14+00:00","read_at_is":"when the build read Syntology's graph, not when any sample ran","claim":"Per-sample execution status on synthesized fixtures; not a correctness claim about the paper. Samples come from repositories linked to the paper, official or community; repo_kind says which.","repos":[{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/shallowdream204/SODA-SR","reach":{"status":"ok","spdx":"Apache-2.0"}}],"summary":{"ran_fixture":1,"ran_draft_wrong":2,"ran_honours":2,"ran":1,"unverified":6},"by_repo_kind":{"official":{"samples":12,"ran":6,"repositories":1}},"repo_kind_vocabulary":{"official":"The archive marks this repository official for the paper","named_in_paper":"The archive records that the paper mentions this repository; it is not marked official","listed":"In the archive's code links for this paper, not marked official and not recorded as mentioned in the paper","found_in_text":"Syntology found this repository in the paper's own text; whether it is the authors' implementation is not asserted","community":"Not in the archive's code links for this paper; a community repository Syntology harvested"},"n_pointer_only_for_licence":0,"samples":[{"code_sha256_prefix":"144d10b49baeb8a6","entry":"window_partition","repo":"shallowdream204/SODA-SR","repo_kind":"official","path":"models/network_soda.py","file_url":"https://github.com/shallowdream204/SODA-SR/blob/HEAD/models/network_soda.py","link_basis":"harvester_set","language":"python","status":"ran_fixture","verification_level":2,"contract_check":"RAISES","metamorphic_tier":"invariant","behaviour_fingerprint":true,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"144d10b49baeb8a6"}},{"code_sha256_prefix":"0bb3503f833a6f8e","entry":"conv","repo":"shallowdream204/SODA-SR","repo_kind":"official","path":"models/basicblock.py","file_url":"https://github.com/shallowdream204/SODA-SR/blob/HEAD/models/basicblock.py","link_basis":"harvester_set","language":"python","status":"ran_draft_wrong","verification_level":1,"contract_check":"OUTPUT_MISDECLARED","metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"0bb3503f833a6f8e"}},{"code_sha256_prefix":"6154e3744ece5728","entry":"create_window","repo":"shallowdream204/SODA-SR","repo_kind":"official","path":"models/loss_ssim.py","file_url":"https://github.com/shallowdream204/SODA-SR/blob/HEAD/models/loss_ssim.py","link_basis":"harvester_set","language":"python","status":"ran_honours","verification_level":1,"contract_check":"HONOURS","metamorphic_tier":"well_formed","behaviour_fingerprint":true,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"6154e3744ece5728"}},{"code_sha256_prefix":"c56b7ef16f309a45","entry":"gaussian","repo":"shallowdream204/SODA-SR","repo_kind":"official","path":"models/loss_ssim.py","file_url":"https://github.com/shallowdream204/SODA-SR/blob/HEAD/models/loss_ssim.py","link_basis":"harvester_set","language":"python","status":"ran_honours","verification_level":1,"contract_check":"HONOURS","metamorphic_tier":"well_formed","behaviour_fingerprint":true,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"c56b7ef16f309a45"}},{"code_sha256_prefix":"1e826b826044c581","entry":"upsample_pixelshuffle","repo":"shallowdream204/SODA-SR","repo_kind":"official","path":"models/basicblock.py","file_url":"https://github.com/shallowdream204/SODA-SR/blob/HEAD/models/basicblock.py","link_basis":"harvester_set","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"1e826b826044c581"}},{"code_sha256_prefix":"61bf152e6a42a184","entry":"window_reverse","repo":"shallowdream204/SODA-SR","repo_kind":"official","path":"models/network_soda.py","file_url":"https://github.com/shallowdream204/SODA-SR/blob/HEAD/models/network_soda.py","link_basis":"harvester_set","language":"python","status":"ran_draft_wrong","verification_level":1,"contract_check":"MISDECLARED","metamorphic_tier":"invariant","behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"61bf152e6a42a184"}},{"code_sha256_prefix":"d290bf91cc78c038","entry":"g_path_regularize","repo":"shallowdream204/SODA-SR","repo_kind":"official","path":"models/loss.py","file_url":"https://github.com/shallowdream204/SODA-SR/blob/HEAD/models/loss.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"d290bf91cc78c038"}},{"code_sha256_prefix":"fe4acbd5f88b4231","entry":"get_valid_ratio","repo":"shallowdream204/SODA-SR","repo_kind":"official","path":"models/network_soda.py","file_url":"https://github.com/shallowdream204/SODA-SR/blob/HEAD/models/network_soda.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"fe4acbd5f88b4231"}},{"code_sha256_prefix":"370bd3c6bf3bd496","entry":"gradient_penalty_loss","repo":"shallowdream204/SODA-SR","repo_kind":"official","path":"models/loss.py","file_url":"https://github.com/shallowdream204/SODA-SR/blob/HEAD/models/loss.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"370bd3c6bf3bd496"}},{"code_sha256_prefix":"e84da58ba9736585","entry":"pixel_unshuffle","repo":"shallowdream204/SODA-SR","repo_kind":"official","path":"models/basicblock.py","file_url":"https://github.com/shallowdream204/SODA-SR/blob/HEAD/models/basicblock.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"e84da58ba9736585"}},{"code_sha256_prefix":"7dfb6088a1ae2d27","entry":"r1_penalty","repo":"shallowdream204/SODA-SR","repo_kind":"official","path":"models/loss.py","file_url":"https://github.com/shallowdream204/SODA-SR/blob/HEAD/models/loss.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"7dfb6088a1ae2d27"}},{"code_sha256_prefix":"9151c793f90473f0","entry":"ssim","repo":"shallowdream204/SODA-SR","repo_kind":"official","path":"models/loss_ssim.py","file_url":"https://github.com/shallowdream204/SODA-SR/blob/HEAD/models/loss_ssim.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"9151c793f90473f0"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}