{"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/generalize-or-detect-towards-robust-semantic","title":"Generalize or Detect? Towards Robust Semantic Segmentation Under Multiple Distribution Shifts","arxiv_id":"2411.03829","date":"2024-11-06","proceeding":null,"authors":["Zhitong Gao","Bingnan Li","Mathieu Salzmann","Xuming He"],"abstract":"In open-world scenarios, where both novel classes and domains may exist, an ideal segmentation model should detect anomaly classes for safety and generalize to new domains. However, existing methods often struggle to distinguish between domain-level and semantic-level distribution shifts, leading to poor out-of-distribution (OOD) detection or domain generalization performance. In this work, we aim to equip the model to generalize effectively to covariate-shift regions while precisely identifying semantic-shift regions. To achieve this, we design a novel generative augmentation method to produce coherent images that incorporate both anomaly (or novel) objects and various covariate shifts at both image and object levels. Furthermore, we introduce a training strategy that recalibrates uncertainty specifically for semantic shifts and enhances the feature extractor to align features associated with domain shifts. We validate the effectiveness of our method across benchmarks featuring both semantic and domain shifts. Our method achieves state-of-the-art performance across all benchmarks for both OOD detection and domain generalization. Code is available at https://github.com/gaozhitong/MultiShiftSeg.","url_abs":"https://arxiv.org/abs/2411.03829v1","url_pdf":"https://arxiv.org/pdf/2411.03829v1.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":"generalize-or-detect-towards-robust-semantic","repo_url":"https://github.com/gaozhitong/multishiftseg","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok","spdx":"Apache-2.0"}}],"tasks":[{"task_slug":"domain-generalization","task_name":"Domain Generalization"},{"task_slug":"ood-detection","task_name":"Out of Distribution (OOD) Detection"},{"task_slug":"semantic-segmentation","task_name":"Semantic Segmentation"}],"methods":[{"method_slug":"align","method_name":"ALIGN"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=2411.03829","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2411.03829"}},"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/gaozhitong/multishiftseg","reach":{"status":"ok","spdx":"Apache-2.0"}}],"summary":{"ran_violates":1,"unverified":3},"by_repo_kind":{"official":{"samples":4,"ran":1,"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":"17cb5b0dfa01b491","entry":"normalize","repo":"gaozhitong/multishiftseg","repo_kind":"official","path":"lib/utils/img_utils.py","file_url":"https://github.com/gaozhitong/multishiftseg/blob/HEAD/lib/utils/img_utils.py","link_basis":"plan_row","language":"python","status":"ran_violates","verification_level":1,"contract_check":"VIOLATES","metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"17cb5b0dfa01b491"}},{"code_sha256_prefix":"830d4a1efb0b5f83","entry":"paste_coco_objects","repo":"gaozhitong/multishiftseg","repo_kind":"official","path":"lib/utils/img_utils.py","file_url":"https://github.com/gaozhitong/multishiftseg/blob/HEAD/lib/utils/img_utils.py","link_basis":"first_harvest_node","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":"830d4a1efb0b5f83"}},{"code_sha256_prefix":"e7acf7ab7267fd2a","entry":"random_scale","repo":"gaozhitong/multishiftseg","repo_kind":"official","path":"lib/utils/img_utils.py","file_url":"https://github.com/gaozhitong/multishiftseg/blob/HEAD/lib/utils/img_utils.py","link_basis":"first_harvest_node","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":"e7acf7ab7267fd2a"}},{"code_sha256_prefix":"610e1afec71039e3","entry":"update_config","repo":"gaozhitong/multishiftseg","repo_kind":"official","path":"lib/configs/config.py","file_url":"https://github.com/gaozhitong/multishiftseg/blob/HEAD/lib/configs/config.py","link_basis":"first_harvest_node","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":"610e1afec71039e3"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}