{"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/comprehensive-multi-modal-interactions-for","title":"Comprehensive Multi-Modal Interactions for Referring Image Segmentation","arxiv_id":"2104.10412","date":"2021-04-21","proceeding":"Findings (ACL) 2022 5","authors":["Kanishk Jain","Vineet Gandhi"],"abstract":"We investigate Referring Image Segmentation (RIS), which outputs a segmentation map corresponding to the natural language description. Addressing RIS efficiently requires considering the interactions happening across visual and linguistic modalities and the interactions within each modality. Existing methods are limited because they either compute different forms of interactions sequentially (leading to error propagation) or ignore intramodal interactions. We address this limitation by performing all three interactions simultaneously through a Synchronous Multi-Modal Fusion Module (SFM). Moreover, to produce refined segmentation masks, we propose a novel Hierarchical Cross-Modal Aggregation Module (HCAM), where linguistic features facilitate the exchange of contextual information across the visual hierarchy. We present thorough ablation studies and validate our approach's performance on four benchmark datasets, showing considerable performance gains over the existing state-of-the-art (SOTA) methods.","url_abs":"https://arxiv.org/abs/2104.10412v4","url_pdf":"https://arxiv.org/pdf/2104.10412v4.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":"comprehensive-multi-modal-interactions-for","repo_url":"https://github.com/kanji95/SHNET","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"pytorch","reach":{"status":"ok"}}],"tasks":[{"task_slug":"image-segmentation","task_name":"Image Segmentation"},{"task_slug":"referring-expression-segmentation","task_name":"Referring Expression Segmentation"},{"task_slug":"segmentation","task_name":"Segmentation"},{"task_slug":"semantic-segmentation","task_name":"Semantic Segmentation"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/referring-expression-segmentation-on-refcoco-5","task":"Referring Expression Segmentation","dataset":"RefCOCO+ test B","model":"SHNet","rank_in_archive_order":22,"of":30,"metrics":{"Overall IoU":"44.12"},"uses_additional_data":false},{"leaderboard":"/sota/referring-expression-segmentation-on-refcoco-4","task":"Referring Expression Segmentation","dataset":"RefCOCO+ testA","model":"SHNet","rank_in_archive_order":23,"of":30,"metrics":{"Overall IoU":"58.46"},"uses_additional_data":false},{"leaderboard":"/sota/referring-expression-segmentation-on-refcoco-3","task":"Referring Expression Segmentation","dataset":"RefCOCO+ val","model":"SHNet","rank_in_archive_order":26,"of":33,"metrics":{"Overall IoU":"52.75"},"uses_additional_data":false},{"leaderboard":"/sota/referring-expression-segmentation-on-refcocog","task":"Referring Expression Segmentation","dataset":"RefCOCOg-val","model":"SHNet","rank_in_archive_order":21,"of":23,"metrics":{"Overall IoU":"49.90"},"uses_additional_data":false},{"leaderboard":"/sota/referring-expression-segmentation-on-refcoco","task":"Referring Expression Segmentation","dataset":"RefCoCo val","model":"SHNet","rank_in_archive_order":28,"of":37,"metrics":{"Overall IoU":"65.32","Precision@0.5":"75.18","Precision@0.6":"69.36","Precision@0.7":"61.21","Precision@0.8":"46.16","Precision@0.9":"16.23"},"uses_additional_data":false},{"leaderboard":"/sota/referring-expression-segmentation-on-referit","task":"Referring Expression Segmentation","dataset":"ReferIt","model":"SHNet","rank_in_archive_order":3,"of":3,"metrics":{"Overall IoU":"69.19"},"uses_additional_data":false}],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=2104.10412","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}