{"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/compact-bilinear-pooling","title":"Compact Bilinear Pooling","arxiv_id":"1511.06062","date":"2015-11-19","proceeding":"CVPR 2016 6","authors":["Yang Gao","Oscar Beijbom","Ning Zhang","Trevor Darrell"],"abstract":"Bilinear models has been shown to achieve impressive performance on a wide\nrange of visual tasks, such as semantic segmentation, fine grained recognition\nand face recognition. However, bilinear features are high dimensional,\ntypically on the order of hundreds of thousands to a few million, which makes\nthem impractical for subsequent analysis. We propose two compact bilinear\nrepresentations with the same discriminative power as the full bilinear\nrepresentation but with only a few thousand dimensions. Our compact\nrepresentations allow back-propagation of classification errors enabling an\nend-to-end optimization of the visual recognition system. The compact bilinear\nrepresentations are derived through a novel kernelized analysis of bilinear\npooling which provide insights into the discriminative power of bilinear\npooling, and a platform for further research in compact pooling methods.\nExperimentation illustrate the utility of the proposed representations for\nimage classification and few-shot learning across several datasets.","url_abs":"http://arxiv.org/abs/1511.06062v2","url_pdf":"http://arxiv.org/pdf/1511.06062v2.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":"compact-bilinear-pooling","repo_url":"https://github.com/gy20073/compact_bilinear_pooling","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"tf","reach":{"status":"ok"}},{"paper_slug":"compact-bilinear-pooling","repo_url":"https://github.com/Seth-Park/MultimodalExplanations","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"caffe2","reach":null},{"paper_slug":"compact-bilinear-pooling","repo_url":"https://github.com/akirafukui/vqa-mcb","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"caffe2","reach":{"status":"ok","spdx":"BSD-2-Clause"}},{"paper_slug":"compact-bilinear-pooling","repo_url":"https://github.com/aniket03/keras_compact_bilnear_CNN","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok"}},{"paper_slug":"compact-bilinear-pooling","repo_url":"https://github.com/divelab/vqa-text","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"caffe2","reach":{"status":"ok"}},{"paper_slug":"compact-bilinear-pooling","repo_url":"https://github.com/jnhwkim/cbp","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"torch","reach":{"status":"ok","spdx":"NOASSERTION"}},{"paper_slug":"compact-bilinear-pooling","repo_url":"https://github.com/Recognito-Vision/Android-FaceRecognition-FaceLivenessDetection","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"none","reach":{"status":"ok"}}],"tasks":[{"task_slug":"face-recognition","task_name":"Face Recognition"},{"task_slug":"few-shot-learning","task_name":"Few-Shot Learning"},{"task_slug":"classification","task_name":"General Classification"},{"task_slug":"image-classification","task_name":"Image Classification"},{"task_slug":"semantic-segmentation","task_name":"Semantic Segmentation"},{"task_slug":"image-classification","task_name":"image-classification"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1511.06062","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}