{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T05:04:47Z","timestamp":1750309487040,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":41,"publisher":"ACM","license":[{"start":{"date-parts":[[2024,10,28]],"date-time":"2024-10-28T00:00:00Z","timestamp":1730073600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2024,10,28]]},"DOI":"10.1145\/3664647.3680991","type":"proceedings-article","created":{"date-parts":[[2024,10,26]],"date-time":"2024-10-26T06:59:33Z","timestamp":1729925973000},"page":"3056-3064","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["CBNet: Cooperation-Based Weakly Supervised Polyp Detection"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7913-7605","authenticated-orcid":false,"given":"Xiuquan","family":"Du","sequence":"first","affiliation":[{"name":"Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education, School of Computer Science and Technology, Anhui University, Hefei, Anhui, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-1113-2080","authenticated-orcid":false,"given":"Jiajia","family":"Chen","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Anhui University, Hefei, Anhui, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-1734-9554","authenticated-orcid":false,"given":"Xuejun","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Anhui University, Hefei, Anhui, China"}]}],"member":"320","published-online":{"date-parts":[[2024,10,28]]},"reference":[{"key":"e_1_3_2_1_1_1","volume-title":"Proceedings of the 15th European Conference on Computer Vision. Springer, 370--386","author":"Yuille","year":"2018","unstructured":"Yuille A. 2018. Weakly supervised region proposal network and object detection. In Proceedings of the 15th European Conference on Computer Vision. Springer, 370--386."},{"key":"e_1_3_2_1_2_1","volume-title":"Grad-CAM: Generalized Gradient-Based Visual Explanations for Deep Convolutional Networks. In IEEE Winter Conference on Applications of Computer Vision. 839--847","author":"Aditya Chattopadhay","year":"2018","unstructured":"Chattopadhay Aditya, Sarkar Anirban, Howlader Prantik, and Balasubramanian Vineeth N. 2018. Grad-CAM: Generalized Gradient-Based Visual Explanations for Deep Convolutional Networks. In IEEE Winter Conference on Applications of Computer Vision. 839--847."},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.compmedimag.2015.02.007"},{"key":"e_1_3_2_1_4_1","volume-title":"Higgins","author":"Chang Qi","year":"2022","unstructured":"Qi Chang, Danish Ahmad, Jennifer Toth, Rebecca Bascom, and William E. Higgins. 2022. ESFPNet: efficient deep learning architecture for real-time lesion segmentation in autofluorescence bronchoscopic video. arXiv preprint arXiv:2207.07759 (2022)."},{"key":"e_1_3_2_1_5_1","volume-title":"Chen Change Loy, and Dahua Lin","author":"Chen Kai","year":"2019","unstructured":"Kai Chen, Jiaqi Wang, Jiangmiao Pang, Yuhang Cao, Yu Xiong, Xiaoxiao Li, Shuyang Sun, Wansen Feng, Ziwei Liu, Jiarui Xu, Zheng Zhang, Dazhi Cheng, Chenchen Zhu, Tianheng Cheng, Qijie Zhao, Buyu Li, Xin Lu, Rui Zhu, Yue Wu, Jifeng Dai, Jingdong Wang, Jianping Shi, Wanli Ouyang, Chen Change Loy, and Dahua Lin. 2019. MMDetection: Open MMLab Detection Toolbox and Benchmark. arXiv preprint arXiv:1906.07155 (2019)."},{"key":"e_1_3_2_1_6_1","volume-title":"DiffusionDet: Diffusion Model for Object Detection. arXiv preprint arXiv:2211.09788","author":"Chen Shoufa","year":"2022","unstructured":"Shoufa Chen, Pei Sun, Yibing Song, and Ping Luo. 2022. DiffusionDet: Diffusion Model for Object Detection. arXiv preprint arXiv:2211.09788 (2022)."},{"key":"e_1_3_2_1_7_1","volume-title":"Extracting Class Activation Maps from Non-Discriminative Features as well. arXiv preprint arXiv:2303.10334","author":"Chen Zhaozheng","year":"2023","unstructured":"Zhaozheng Chen and Qianru Sun. 2023. Extracting Class Activation Maps from Non-Discriminative Features as well. arXiv preprint arXiv:2303.10334 (2023)."},{"key":"e_1_3_2_1_8_1","volume-title":"Proceedings of the European conference on computer vision (ECCV)","author":"Zitnick","year":"2014","unstructured":"Zitnick C.L and Doll\u00b4ar P. 2014. Edge boxes: Locating object proposals from edges. In Proceedings of the European conference on computer vision (ECCV) (2014), 391--405."},{"key":"e_1_3_2_1_9_1","volume-title":"Johansen Dag, and Johansen H\u00e5vard D.","author":"Debesh Ha","year":"2020","unstructured":"Ha Debesh, Pia H. Smedsrud, Michael A. Riegler, Halvorsen P\u00e5l, De Lange Thomas, Johansen Dag, and Johansen H\u00e5vard D. 2020. Kvasir-seg: A segmented polyp dataset. In MultiMedia Modeling. 451--462."},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-012-0538-3"},{"key":"e_1_3_2_1_11_1","volume-title":"Proceedings of the European conference on computer vision (ECCV)","author":"Eungyeup Kim","year":"2021","unstructured":"Kim Eungyeup, Lee Jihyeon, and Choo Jaegul. 2021. BiaSwap: Removing dataset bias with bias-tailored swapping augmentation. In Proceedings of the European conference on computer vision (ECCV) (2021)."},{"key":"e_1_3_2_1_12_1","first-page":"122","article-title":"Discrepant multiple instance learning for weakly supervised object detection","volume":"122","author":"Gao Wei","year":"2022","unstructured":"Wei Gao, Fang Wan, Jun Yue, Songcen Xu, and Qixiang Ye. 2022. Discrepant multiple instance learning for weakly supervised object detection. Pattern Recognition: The Journal of the Pattern Recognition Society 122 (2022), 122.","journal-title":"Pattern Recognition: The Journal of the Pattern Recognition Society"},{"key":"e_1_3_2_1_13_1","volume-title":"Weakly Supervised Deep Detection Networks. In IEEE Conference on Computer Vision and Pattern Recognition. 2846--2854","author":"Hakan Bilen","year":"2016","unstructured":"Bilen Hakan and Vedaldi Andrea. 2016. Weakly Supervised Deep Detection Networks. In IEEE Conference on Computer Vision and Pattern Recognition. 2846--2854."},{"key":"e_1_3_2_1_14_1","volume-title":"RIGOR: Recycling inference in graph cuts for generating object regions. Pattern Recognition: The Journal of the Pattern Recognition Society","author":"Humayun Ahmad","year":"2014","unstructured":"Ahmad Humayun, Fuxin Li, and James M Rehg. 2014. RIGOR: Recycling inference in graph cuts for generating object regions. Pattern Recognition: The Journal of the Pattern Recognition Society (2014), 336--343."},{"key":"e_1_3_2_1_15_1","volume-title":"ECC-PolypDet: Enhanced CenterNet with Contrastive Learning for Automatic Polyp Detection. arXiv preprint arXiv:2401.04961","author":"Jiang Yuncheng","year":"2024","unstructured":"Yuncheng Jiang, Zixun Zhang, Yiwen Hu, Guanbin Li, Xiang Wan, and Song Wu. 2024. ECC-PolypDet: Enhanced CenterNet with Contrastive Learning for Automatic Polyp Detection. arXiv preprint arXiv:2401.04961 (2024)."},{"key":"e_1_3_2_1_16_1","volume-title":"International Joint Conference on Artificial Intelligence,- IJCAI","volume":"104","author":"Uijlings J.R","year":"2013","unstructured":"Uijlings J.R, van de Sande K.E, Gevers T., and Smeulders A.W. 2013. Selective search for object recognition. International Joint Conference on Artificial Intelligence,- IJCAI, Vol. 104, 2 (2013), 154--171."},{"key":"e_1_3_2_1_17_1","volume-title":"Segment anything in medical images. Nature Communications (Jan","author":"Jun Ma","year":"2024","unstructured":"Ma Jun, Yuting He, Li Feifei, Han Lin, Chenyu You, and Bo Wang. 2024. Segment anything in medical images. Nature Communications (Jan. 2024)."},{"key":"e_1_3_2_1_18_1","volume-title":"Refine-FPN: Instance Segmentation Based on a Non-local Multi-feature Aggregation Mechanism. Neural processing letters","author":"Li Xiaolian","year":"2023","unstructured":"Xiaolian Li, Lei Zhu, Wenwu Wang, and Ke Yang. 2023. Refine-FPN: Instance Segmentation Based on a Non-local Multi-feature Aggregation Mechanism. Neural processing letters (2023)."},{"key":"e_1_3_2_1_19_1","volume-title":"Polyp-sam: Transfer sam for polyp segmentation. arXiv preprint arXiv:2305.00293","author":"Li Yuheng","year":"2023","unstructured":"Yuheng Li, Mingzhe Hu, and Xiaofeng Yang. 2023. Polyp-sam: Transfer sam for polyp segmentation. arXiv preprint arXiv:2305.00293 (2023)."},{"key":"e_1_3_2_1_20_1","volume-title":"A Survey on Deep Learning for Polyp Segmentation: Techniques, Challenges and Future Trends. arXiv preprint arXiv:2311.18373","author":"Mei Jiaxin","year":"2023","unstructured":"Jiaxin Mei, Tao Zhou, Kaiwen Huang, Yizhe Zhang, Yi Zhou, Ye Wu, and Huazhu Fu. 2023. A Survey on Deep Learning for Polyp Segmentation: Techniques, Challenges and Future Trends. arXiv preprint arXiv:2311.18373 (2023)."},{"key":"e_1_3_2_1_21_1","volume-title":"Anatomy-Driven Pathology Detection on Chest X-rays. In International MICCAI Brainlesion Workshop","author":"M\u00fcller Philip","year":"2023","unstructured":"Philip M\u00fcller, Felix Meissen, Johannes Brandt, Georgios Kaissis, and Daniel Rueckert. 2023. Anatomy-Driven Pathology Detection on Chest X-rays. In International MICCAI Brainlesion Workshop (2023)."},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.3390\/diseases11040148"},{"key":"e_1_3_2_1_23_1","volume-title":"International Journal of Computer Vision","author":"Olga Russakovsky","year":"2014","unstructured":"Russakovsky Olga, Jia Deng, Hao Su, Krause Jonathan, Satheesh Sanjeev, Ma Sean, Zhiheng Huang, Karpathy Andrej, Khosla Aditya, and Bernstein Michael. 2014. ImageNet Large Scale Visual Recognition Challenge. International Journal of Computer Vision (2014), 1--42."},{"key":"e_1_3_2_1_24_1","volume-title":"Accurate Real-time Polyp Detection in Videos from Concatenation of Latent Features Extracted from Consecutive Frames. arXiv preprint arXiv:2303.05871","author":"Qadir Hemin Ali","year":"2023","unstructured":"Hemin Ali Qadir, Younghak Shin, Jacob Bergsland, and Ilangko Balasingham. 2023. Accurate Real-time Polyp Detection in Videos from Concatenation of Latent Features Extracted from Consecutive Frames. arXiv preprint arXiv:2303.05871 (2023)."},{"key":"e_1_3_2_1_25_1","volume-title":"Generalized pancreatic cancer diagnosis via multiple instance learning and anatomically-guided shape normalization. Medical Image Analysis (May","author":"Qu Jiaqi","year":"2023","unstructured":"Jiaqi Qu, Xunbin Wei, and Xiaohua Qian. 2023. Generalized pancreatic cancer diagnosis via multiple instance learning and anatomically-guided shape normalization. Medical Image Analysis (May 2023)."},{"volume-title":"Proceedings of the IEEE 1st International Conference on Broadnets Networks (BroadNets'04)","author":"Rahman M. M.","key":"e_1_3_2_1_26_1","unstructured":"M. M. Rahman and R. Marculescu. 2023. Medical image segmentation via cascaded attention decoding. In Proceedings of the IEEE 1st International Conference on Broadnets Networks (BroadNets'04). IEEE, CVF WACVW, 6222--6231."},{"key":"e_1_3_2_1_27_1","volume-title":"YOLOv3: An Incremental Improvement. arXiv preprint arXiv:1804.02767","author":"Redmon Joseph","year":"2018","unstructured":"Joseph Redmon and Ali Farhadi. 2018. YOLOv3: An Incremental Improvement. arXiv preprint arXiv:1804.02767 (2018)."},{"key":"e_1_3_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2016.2577031"},{"key":"e_1_3_2_1_29_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.74"},{"key":"e_1_3_2_1_30_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00079"},{"key":"e_1_3_2_1_31_1","volume-title":"Global cancer statistics 2020: Globocan estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA: a cancer journal for clinicians","author":"Sung Hyuna","year":"2021","unstructured":"Hyuna Sung, Jacques Ferlay, Rebecca L Siegel, Mathieu Laversanne, Isabelle Soerjomataram, Ahmedin Jemal, and Freddie Bray. 2021. Global cancer statistics 2020: Globocan estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA: a cancer journal for clinicians, Vol. 71, 3 (2021), 209--249."},{"key":"e_1_3_2_1_32_1","volume-title":"Multiple Instance Detection Network with Online Instance Classifier Refinement. In IEEE Conference on Computer Vision and Pattern Recognition. 3059--3067","author":"Tang Peng","year":"2017","unstructured":"Peng Tang, Xinggang Wang, Xiang Bai, and Wenyu Liu. 2017. Multiple Instance Detection Network with Online Instance Classifier Refinement. In IEEE Conference on Computer Vision and Pattern Recognition. 3059--3067."},{"key":"e_1_3_2_1_33_1","volume-title":"Tganet: Text-guided attention for improved polyp segmentation. In In International MICCAI Brainlesion Workshop","author":"Tomar N. K.","year":"2022","unstructured":"N. K. Tomar, U. Bagci D. Jha,, and S. Ali. 2022. Tganet: Text-guided attention for improved polyp segmentation. In In International MICCAI Brainlesion Workshop. Springer, 151--160."},{"key":"e_1_3_2_1_34_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2024.3356174"},{"key":"e_1_3_2_1_35_1","volume-title":"Absolute Wrong Makes Better: Boosting Weakly Supervised Object Detection via Negative Deterministic Information. arXiv preprint arXiv:2204.10068","author":"Wang Guanchun","year":"2022","unstructured":"Guanchun Wang, Xiangrong Zhang, Zelin Peng, Xu Tang, Huiyu Zhou, and Licheng Jiao. 2022. Absolute Wrong Makes Better: Boosting Weakly Supervised Object Detection via Negative Deterministic Information. arXiv preprint arXiv:2204.10068 (2022)."},{"key":"e_1_3_2_1_36_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-16437-8_11"},{"key":"e_1_3_2_1_37_1","doi-asserted-by":"publisher","DOI":"10.1053\/j.gastro.2020.06.023"},{"key":"e_1_3_2_1_38_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2021.3056887"},{"key":"e_1_3_2_1_39_1","doi-asserted-by":"crossref","unstructured":"Su Z Tavolara TE Carreno-Galeano G Lee SJ Gurcan MN and Niazi MKK. 2022. Attention2majority: Weak multiple instance learning for regenerative kidney grading on whole slide images. Medical Image Analysis (April 2022).","DOI":"10.1016\/j.media.2022.102462"},{"key":"e_1_3_2_1_40_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00838"},{"key":"e_1_3_2_1_41_1","volume-title":"Can SAM Segment Polyps? arXiv preprint arXiv:2311.18373","author":"Zhou Tao","year":"2023","unstructured":"Tao Zhou, Yizhe Zhang, Yi Zhou, Ye Wu, and Chen Gong. 2023. Can SAM Segment Polyps? arXiv preprint arXiv:2311.18373 (2023)."}],"event":{"name":"MM '24: The 32nd ACM International Conference on Multimedia","sponsor":["SIGMM ACM Special Interest Group on Multimedia"],"location":"Melbourne VIC Australia","acronym":"MM '24"},"container-title":["Proceedings of the 32nd ACM International Conference on Multimedia"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3664647.3680991","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3664647.3680991","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T01:17:35Z","timestamp":1750295855000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3664647.3680991"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,10,28]]},"references-count":41,"alternative-id":["10.1145\/3664647.3680991","10.1145\/3664647"],"URL":"https:\/\/doi.org\/10.1145\/3664647.3680991","relation":{},"subject":[],"published":{"date-parts":[[2024,10,28]]},"assertion":[{"value":"2024-10-28","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}