{"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/sgat4pass-spherical-geometry-aware","title":"SGAT4PASS: Spherical Geometry-Aware Transformer for PAnoramic Semantic Segmentation","arxiv_id":"2306.03403","date":"2023-06-06","proceeding":null,"authors":["XueWei Li","Tao Wu","Zhongang Qi","Gaoang Wang","Ying Shan","Xi Li"],"abstract":"As an important and challenging problem in computer vision, PAnoramic Semantic Segmentation (PASS) gives complete scene perception based on an ultra-wide angle of view. Usually, prevalent PASS methods with 2D panoramic image input focus on solving image distortions but lack consideration of the 3D properties of original $360^{\\circ}$ data. Therefore, their performance will drop a lot when inputting panoramic images with the 3D disturbance. To be more robust to 3D disturbance, we propose our Spherical Geometry-Aware Transformer for PAnoramic Semantic Segmentation (SGAT4PASS), considering 3D spherical geometry knowledge. Specifically, a spherical geometry-aware framework is proposed for PASS. It includes three modules, i.e., spherical geometry-aware image projection, spherical deformable patch embedding, and a panorama-aware loss, which takes input images with 3D disturbance into account, adds a spherical geometry-aware constraint on the existing deformable patch embedding, and indicates the pixel density of original $360^{\\circ}$ data, respectively. Experimental results on Stanford2D3D Panoramic datasets show that SGAT4PASS significantly improves performance and robustness, with approximately a 2% increase in mIoU, and when small 3D disturbances occur in the data, the stability of our performance is improved by an order of magnitude. Our code and supplementary material are available at https://github.com/TencentARC/SGAT4PASS.","url_abs":"https://arxiv.org/abs/2306.03403v2","url_pdf":"https://arxiv.org/pdf/2306.03403v2.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":"sgat4pass-spherical-geometry-aware","repo_url":"https://github.com/tencentarc/sgat4pass","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok","spdx":"Apache-2.0"}}],"tasks":[{"task_slug":"semantic-segmentation","task_name":"Semantic Segmentation"}],"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":"focus","method_name":"Focus"},{"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":[{"leaderboard":"/sota/semantic-segmentation-on-stanford2d3d-1","task":"Semantic Segmentation","dataset":"Stanford2D3D Panoramic","model":"SGAT4PASS（RGB only, Fold 1）","rank_in_archive_order":4,"of":25,"metrics":{"mIoU":"56.4%"},"uses_additional_data":false},{"leaderboard":"/sota/semantic-segmentation-on-stanford2d3d-1","task":"Semantic Segmentation","dataset":"Stanford2D3D Panoramic","model":"SGAT4PASS（RGB only, 3 Fold AVG）","rank_in_archive_order":6,"of":25,"metrics":{"mIoU":"55.3%"},"uses_additional_data":false}],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=2306.03403","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2306.03403"}},"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":"deterministic:regex_extraction","url":"https://github.com/TencentARC/SGAT4PASS","reach":{"status":"ok","spdx":"Apache-2.0"}}],"summary":{"ran":3,"ran_fixture":4,"ran_violates":1,"unverified":3},"by_repo_kind":{"official":{"samples":11,"ran":8,"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":9,"samples":[{"code_sha256_prefix":"33efc9f1ccc7933c","entry":"drop_block_2d","repo":"TencentARC/SGAT4PASS","repo_kind":"official","path":"segmentron/modules/drop.py","file_url":"https://github.com/TencentARC/SGAT4PASS/blob/HEAD/segmentron/modules/drop.py","link_basis":"plan_row","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":"33efc9f1ccc7933c"}},{"code_sha256_prefix":"30d63ccefb97a166","entry":"drop_block_fast_2d","repo":"TencentARC/SGAT4PASS","repo_kind":"official","path":"segmentron/modules/drop.py","file_url":"https://github.com/TencentARC/SGAT4PASS/blob/HEAD/segmentron/modules/drop.py","link_basis":"plan_row","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":"30d63ccefb97a166"}},{"code_sha256_prefix":"3ac6b7d76e8e3584","entry":"drop_path","repo":"TencentARC/SGAT4PASS","repo_kind":"official","path":"segmentron/modules/drop.py","file_url":"https://github.com/TencentARC/SGAT4PASS/blob/HEAD/segmentron/modules/drop.py","link_basis":"harvester_set","language":"python","status":"ran_fixture","verification_level":1,"contract_check":"RAISES","metamorphic_tier":"invariant","behaviour_fingerprint":true,"licence":"Apache-2.0","inline_ok":false,"mcp_get_code":{"code_sha256":"3ac6b7d76e8e3584"}},{"code_sha256_prefix":"d94639b28b2134ff","entry":"iou","repo":"TencentARC/SGAT4PASS","repo_kind":"official","path":"segmentron/solver/lovasz_losses.py","file_url":"https://github.com/TencentARC/SGAT4PASS/blob/HEAD/segmentron/solver/lovasz_losses.py","link_basis":"harvester_set","language":"python","status":"ran_fixture","verification_level":1,"contract_check":"RAISES","metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"Apache-2.0","inline_ok":false,"mcp_get_code":{"code_sha256":"d94639b28b2134ff"}},{"code_sha256_prefix":"1211530cd527bd0b","entry":"iou_binary","repo":"TencentARC/SGAT4PASS","repo_kind":"official","path":"segmentron/solver/lovasz_losses.py","file_url":"https://github.com/TencentARC/SGAT4PASS/blob/HEAD/segmentron/solver/lovasz_losses.py","link_basis":"harvester_set","language":"python","status":"ran_fixture","verification_level":1,"contract_check":"RAISES","metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"Apache-2.0","inline_ok":false,"mcp_get_code":{"code_sha256":"1211530cd527bd0b"}},{"code_sha256_prefix":"e85b5d21dc5b8382","entry":"lovasz_grad","repo":"TencentARC/SGAT4PASS","repo_kind":"official","path":"segmentron/solver/lovasz_losses.py","file_url":"https://github.com/TencentARC/SGAT4PASS/blob/HEAD/segmentron/solver/lovasz_losses.py","link_basis":"harvester_set","language":"python","status":"ran_violates","verification_level":1,"contract_check":"VIOLATES","metamorphic_tier":"invariant","behaviour_fingerprint":true,"licence":"Apache-2.0","inline_ok":false,"mcp_get_code":{"code_sha256":"e85b5d21dc5b8382"}},{"code_sha256_prefix":"5b2c72c30130d62a","entry":"make_divisible","repo":"TencentARC/SGAT4PASS","repo_kind":"official","path":"segmentron/modules/dmlpv2.py","file_url":"https://github.com/TencentARC/SGAT4PASS/blob/HEAD/segmentron/modules/dmlpv2.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":false,"mcp_get_code":{"code_sha256":"5b2c72c30130d62a"}},{"code_sha256_prefix":"02566da69866c48c","entry":"trunc_normal_","repo":"TencentARC/SGAT4PASS","repo_kind":"official","path":"segmentron/modules/norm.py","file_url":"https://github.com/TencentARC/SGAT4PASS/blob/HEAD/segmentron/modules/norm.py","link_basis":"harvester_set","language":"python","status":"ran_fixture","verification_level":1,"contract_check":"RAISES","metamorphic_tier":"invariant","behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":false,"mcp_get_code":{"code_sha256":"02566da69866c48c"}},{"code_sha256_prefix":"7d6250302cdb769d","entry":"get_norm","repo":"TencentARC/SGAT4PASS","repo_kind":"official","path":"segmentron/modules/batch_norm.py","file_url":"https://github.com/TencentARC/SGAT4PASS/blob/HEAD/segmentron/modules/batch_norm.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":false,"mcp_get_code":{"code_sha256":"7d6250302cdb769d"}},{"code_sha256_prefix":"e61675ac705df858","entry":"get_segmentation_loss","repo":"TencentARC/SGAT4PASS","repo_kind":"official","path":"segmentron/solver/loss.py","file_url":"https://github.com/TencentARC/SGAT4PASS/blob/HEAD/segmentron/solver/loss.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":false,"mcp_get_code":{"code_sha256":"e61675ac705df858"}},{"code_sha256_prefix":"644effb1fd52ef7d","entry":"groupNorm","repo":"TencentARC/SGAT4PASS","repo_kind":"official","path":"segmentron/modules/batch_norm.py","file_url":"https://github.com/TencentARC/SGAT4PASS/blob/HEAD/segmentron/modules/batch_norm.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":false,"mcp_get_code":{"code_sha256":"644effb1fd52ef7d"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}