{"type":"ScholarlyArticle","title":"Sph2Pob: Boosting Object Detection on Spherical Images with Planar Oriented Boxes Methods","authors":[{"name":"Xinyuan Liu","slug":"xinyuan-liu","given":"Xinyuan","family":"Liu","affiliation":"Key Laboratory of Intelligent Information Processing of Chinese Academy of Sciences , Institute of Computing Technology , Chinese Academy of Sciences , Beijing , China; University of Chinese Academy of Sciences , Beijing , China"},{"name":"Hang Xu","slug":"hang-xu","given":"Hang","family":"Xu","affiliation":"Hangzhou Dianzi University , Hangzhou , China"},{"name":"Bin Chen","slug":"bin-chen","given":"Bin","family":"Chen","affiliation":"Key Laboratory of Intelligent Information Processing of Chinese Academy of Sciences , Institute of Computing Technology , Chinese Academy of Sciences , Beijing , China; University of Chinese Academy of Sciences , Beijing , China"},{"name":"Qiang Zhao","slug":"qiang-zhao","given":"Qiang","family":"Zhao","affiliation":"Key Laboratory of Intelligent Information Processing of Chinese Academy of Sciences , Institute of Computing Technology , Chinese Academy of Sciences , Beijing , China"},{"name":"Yike Ma","slug":"yike-ma","given":"Yike","family":"Ma","affiliation":"Key Laboratory of Intelligent Information Processing of Chinese Academy of Sciences , Institute of Computing Technology , Chinese Academy of Sciences , Beijing , China"},{"name":"Chenggang Yan","slug":"chenggang-yan","given":"Chenggang","family":"Yan","affiliation":"Hangzhou Dianzi University , Hangzhou , China"},{"name":"Feng Dai","slug":"feng-dai","given":"Feng","family":"Dai","affiliation":"Key Laboratory of Intelligent Information Processing of Chinese Academy of Sciences , Institute of Computing Technology , Chinese Academy of Sciences , Beijing , China"}],"abstract":"Object detection on panoramic/spherical images has been developed rapidly in the past few years, where IoU-calculator is a fundamental part of various detector components, i.e. Label Assignment, Loss and NMS. Due to the low efficiency and non-differentiability of spherical Unbiased IoU, spherical approximate IoU methods have been proposed recently. We find that the key of these approximate methods is to map spherical boxes to planar boxes. However, there exists two problems in these methods: (1) they do not eliminate the influence of panoramic image distortion; (2) they break the original pose between bounding boxes. They lead to the low accuracy of these methods. Taking the two problems into account, we propose a new sphere-plane boxes transform, called Sph2Pob. Based on the Sph2Pob, we propose (1) an differentiable IoU, Sph2Pob-IoU, for spherical boxes with low time-cost and high accuracy and (2) an agent Loss, Sph2Pob-Loss, for spherical detection with high flexibility and expansibility. Extensive experiments verify the effectiveness and generality of our approaches, and Sph2Pob-IoU and Sph2Pob-Loss together boost the performance of spherical detectors. The source code is available at https://github.com/AntXinyuan/sph2pob.","doi":"10.24963/ijcai.2023/137","url":"https://ijcai.org/proceedings/2023/137","pdf":"https://ijcai.org/proceedings/2023/0137.pdf","markdown":"https://ijcai.org/proceedings/2023/137.md","bibtex":"https://ijcai.org/proceedings/2023/bibtex/137","volume":{"slug":"2023","title":"Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2023","url":"https://ijcai.org/proceedings/2023/","year":2023,"location":"Macao, SAR","dates":"19-25 August 2023","editors":"Edith Elkind","isbn":"978-1-956792-03-4","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2023"},"section":"Computer Vision","track":"Main Track","number":137,"pages":{"first":1231,"last":1239},"keywords":["Computer Vision: CV: Recognition (object detection, categorization)","Computer Vision: CV: Machine learning for vision","Computer Vision: CV: Scene analysis and understanding"],"videos":[],"references":[{"position":1,"raw":"[Cao et al., 2022] Miao Cao, Satoshi Ikehata, and Kiyoharu Aizawa. Field-of-view iou for object detection in 360° images. arXiv e-prints, pages arXiv-2202, 2022.","title":"Field-of-view iou for object detection in 360° images","authors":"Satoshi Miao Cao, Kiyoharu Ikehata, Aizawa","year":"2022","venue":null,"doi":null,"url":null,"internal_url":null},{"position":2,"raw":"[Chen et al., 2019] 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. MMDetection: Open mmlab detection toolbox and benchmark. arXiv preprint arXiv:1906.07155, 2019.","title":"MMDetection: Open mmlab detection toolbox and benchmark","authors":"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, Dahua Lin","year":"2019","venue":null,"doi":null,"url":null,"internal_url":null},{"position":3,"raw":"[Chou et al., 2020] Shih-Han Chou, Cheng Sun, Wen-Yen Chang, Wan-Ting Hsu, Min Sun, and Jianlong Fu. 360- indoor: Towards learning real-world objects in 360deg indoor equirectangular images. In Proceedings of the IEEE/CVF Winter Conference on Applications of Com- puter Vision, pages 845-853, 2020.","title":"360indoor: Towards learning real-world objects in 360deg indoor equirectangular images","authors":"Shih-Han Chou, Cheng Sun, Wen-Yen Chang, Wan-Ting Hsu, Min Sun, Jianlong Fu","year":"2020","venue":"Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision","doi":null,"url":null,"internal_url":null},{"position":4,"raw":"[Dai et al., 2021] Pengwen Dai, Sanyi Zhang, Hua Zhang, and Xiaochun Cao. Progressive contour regression for arbitrary-shape scene text detection. In Proceedings of the IEEE/CVF conference on computer vision and pattern recognition, pages 7393-7402, 2021.","title":"Progressive contour regression for arbitrary-shape scene text detection","authors":"Dai","year":"2021","venue":"Proceedings of the IEEE/CVF conference on computer vision and pattern recognition","doi":null,"url":null,"internal_url":null},{"position":5,"raw":"[Dai et al., 2022a] Feng Dai, Bin Chen, Hang Xu, Yike Ma, Xiaodong Li, Bailan Feng, Peng Yuan, Chenggang Yan, and Qiang Zhao. Unbiased iou for spherical image object detection. In Proceedings of AAAI Conference on Artificial Intelligence, pages 508-515, 2022.","title":"Unbiased iou for spherical image object detection","authors":"Dai","year":"2022","venue":"Proceedings of AAAI Conference on Artificial Intelligence","doi":null,"url":null,"internal_url":null},{"position":6,"raw":"[Dai et al., 2022b] Longgang Dai, Hongming Chen, Yufeng Li, Caihua Kong, Zhentao Fan, Jiyang Lu, and Xiang Chen. Tardet: Two-stage anchor-free rotating object de- tector in aerial images. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pages 4267-4275, 2022.","title":"Tardet: Two-stage anchor-free rotating object detector in aerial images","authors":"Dai","year":"2022","venue":"Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition","doi":null,"url":null,"internal_url":null},{"position":7,"raw":"[He et al., 2021] Yuhang He, Wentao Yu, Jie Han, Xing Wei, Xiaopeng Hong, and Yihong Gong. Know your surround- ings: Panoramic multi-object tracking by multimodality collaboration. In Proceedings of the IEEE/CVF Confer- ence on Computer Vision and Pattern Recognition, pages 2969-2980, 2021.","title":"Know your surroundings: Panoramic multi-object tracking by multimodality collaboration","authors":"Yuhang He, Wentao Yu, Jie Han, Xing Wei, Xiaopeng Hong, Yihong Gong","year":"2021","venue":"Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition","doi":null,"url":null,"internal_url":null},{"position":8,"raw":"[Kang and Cho, 2019] Kyoungkook Kang and Sunghyun Cho. Interactive and automatic navigation for 360 video playback. ACM Transactions on Graphics (TOG), 38(4):1-11, 2019.","title":"Interactive and automatic navigation for 360 video playback","authors":"Cho Kang, Kyoungkook Kang, Sunghyun Cho","year":"2019","venue":"ACM Transactions on Graphics (TOG)","doi":null,"url":null,"internal_url":null},{"position":9,"raw":"[Lin et al., 2014] Tsung-Yi Lin, Michael Maire, Serge Be- longie, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollár, and C Lawrence Zitnick. Microsoft coco: Com- mon objects in context. In European conference on com- puter vision, pages 740-755. Springer, 2014.","title":"Microsoft coco: Common objects in context","authors":"Tsung-Yi Lin, Michael Maire, Serge Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollár, C Lawrence, Zitnick","year":"2014","venue":"European conference on computer vision","doi":null,"url":null,"internal_url":null},{"position":10,"raw":"[Lin et al., 2017] Tsung-Yi Lin, Priya Goyal, Ross Girshick, Kaiming He, and Piotr Dollár. Focal loss for dense ob- ject detection. In Proceedings of the IEEE international conference on computer vision, pages 2980-2988, 2017.","title":"Focal loss for dense object detection","authors":"Tsung-Yi Lin, Priya Goyal, Ross Girshick, Kaiming He, Piotr Dollár","year":"2017","venue":"Proceedings of the IEEE international conference on computer vision","doi":null,"url":null,"internal_url":null},{"position":11,"raw":"[Liu et al., 2016] Wei Liu, Dragomir Anguelov, Dumitru Er- han, Christian Szegedy, Scott Reed, Cheng-Yang Fu, and Alexander C Berg. Ssd: Single shot multibox detector. In European conference on computer vision, pages 21-37. Springer, 2016.","title":"Ssd: Single shot multibox detector","authors":"Wei Liu, Dragomir Anguelov, Dumitru Erhan, Christian Szegedy, Scott Reed, Cheng-Yang Fu, Alexander C Berg","year":"2016","venue":"European conference on computer vision","doi":null,"url":null,"internal_url":null},{"position":12,"raw":"[Ma et al., 2018] Jianqi Ma, Weiyuan Shao, Hao Ye, Li Wang, Hong Wang, Yingbin Zheng, and Xiangyang Xue. Arbitrary-oriented scene text detection via ro- tation proposals. IEEE Transactions on Multimedia, 20(11):3111-3122, 2018.","title":"Arbitrary-oriented scene text detection via rotation proposals","authors":"Ma","year":"2018","venue":"IEEE Transactions on Multimedia","doi":null,"url":null,"internal_url":null},{"position":13,"raw":"[Paszke et al., 2017] Adam Paszke, Sam Gross, Soumith Chintala, Gregory Chanan, Edward Yang, Zachary De- Vito, Zeming Lin, Alban Desmaison, Luca Antiga, and Adam Lerer. Automatic differentiation in pytorch. 2017.","title":"Automatic differentiation in pytorch","authors":"Adam Paszke, Sam Gross, Soumith Chintala, Gregory Chanan, Edward Yang, Zachary De-Vito, Zeming Lin, Alban Desmaison, Luca Antiga, Adam Lerer","year":"2017","venue":null,"doi":null,"url":null,"internal_url":null},{"position":14,"raw":"[Ren et al., 2015] Shaoqing Ren, Kaiming He, Ross Gir- shick, and Jian Sun. Faster r-cnn: Towards real-time ob- ject detection with region proposal networks. Advances in neural information processing systems, 28, 2015.","title":"Faster r-cnn: Towards real-time object detection with region proposal networks","authors":"Ren","year":"2015","venue":"Advances in neural information processing systems","doi":null,"url":null,"internal_url":null},{"position":15,"raw":"[Rezatofighi et al., 2019] Hamid Rezatofighi, Nathan Tsoi, JunYoung Gwak, Amir Sadeghian, Ian Reid, and Silvio Savarese. Generalized intersection over union: A metric and a loss for bounding box regression. In Proceedings of the IEEE/CVF conference on computer vision and pattern recognition, pages 658-666, 2019.","title":"Generalized intersection over union: A metric and a loss for bounding box regression","authors":"Hamid Rezatofighi, Nathan Tsoi, Junyoung Gwak, Amir Sadeghian, Ian Reid, Silvio Savarese","year":"2019","venue":"Proceedings of the IEEE/CVF conference on computer vision and pattern recognition","doi":null,"url":null,"internal_url":null},{"position":16,"raw":"[Snyder, 1997] John P Snyder. Flattening the earth: two thousand years of map projections. University of Chicago Press, 1997.","title":"Flattening the earth: two thousand years of map projections","authors":"P John, Snyder","year":"1997","venue":null,"doi":null,"url":null,"internal_url":null},{"position":17,"raw":"[Tian et al., 2019] Zhi Tian, Chunhua Shen, Hao Chen, and Tong He. Fcos: Fully convolutional one-stage object de- tection. In Proceedings of the IEEE/CVF international conference on computer vision, pages 9627-9636, 2019.","title":"Fcos: Fully convolutional one-stage object detection","authors":"Chunhua Zhi Tian, Hao Shen, Tong Chen, He","year":"2019","venue":"Proceedings of the IEEE/CVF international conference on computer vision","doi":null,"url":null,"internal_url":null},{"position":18,"raw":"[Wang and Lai, 2019] Kuan-Hsun Wang and Shang-Hong Lai. Object detection in curved space for 360-degree cam- era. In ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pages 3642-3646. IEEE, 2019.","title":"Object detection in curved space for 360-degree camera","authors":"Wang, Lai ; Kuan-Hsun Wang, Shang-Hong Lai","year":"2019","venue":"ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","doi":null,"url":null,"internal_url":null},{"position":19,"raw":"[Xu et al., 2022] Hang Xu, Qiang Zhao, Yike Ma, Xiaodong Li, Peng Yuan, Bailan Feng, Chenggang Yan, and Feng Dai. Pandora: A panoramic detection dataset for object with orientation. In ECCV, 2022.","title":"Pandora: A panoramic detection dataset for object with orientation","authors":"Hang Xu, Qiang Zhao, Yike Ma, Xiaodong Li, Peng Yuan, Bailan Feng, Chenggang Yan, Feng Dai","year":"2022","venue":"ECCV","doi":null,"url":null,"internal_url":null},{"position":20,"raw":"[Xu et al., 2023] Hang Xu, Xinyuan Liu, Qiang Zhao, Yike Ma, Chenggang Yan, and Feng Dai. Gaussian label distri- bution learning for spherical image object detection. In IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023.","title":"Gaussian label distribution learning for spherical image object detection","authors":"Hang Xu, Xinyuan Liu, Qiang Zhao, Yike Ma, Chenggang Yan, Feng Dai","year":"2023","venue":"IEEE/CVF Conference on Computer Vision and Pattern Recognition","doi":null,"url":null,"internal_url":null},{"position":21,"raw":"[Yang and Yan, 2020] Xue Yang and Junchi Yan. Arbitrary- oriented object detection with circular smooth label. In Eu- ropean Conference on Computer Vision, pages 677-694. Springer, 2020.","title":"Arbitraryoriented object detection with circular smooth label","authors":"Xue Yang, Junchi Yan","year":"2020","venue":"European Conference on Computer Vision","doi":null,"url":null,"internal_url":null},{"position":22,"raw":"[Yang et al., 2018] Xue Yang, Hao Sun, Kun Fu, Jirui Yang, Xian Sun, Menglong Yan, and Zhi Guo. Automatic ship detection in remote sensing images from google earth of complex scenes based on multiscale rotation dense feature pyramid networks. Remote Sensing, 10(1):132, 2018.","title":"Automatic ship detection in remote sensing images from google earth of complex scenes based on multiscale rotation dense feature pyramid networks","authors":"Xue Yang, Hao Sun, Kun Fu, Jirui Yang, Xian Sun, Menglong Yan, Zhi Guo","year":"2018","venue":"Remote Sensing","doi":null,"url":null,"internal_url":null},{"position":23,"raw":"[Yang et al., 2021a] Kailun Yang, Jiaming Zhang, Simon Reiß, Xinxin Hu, and Rainer Stiefelhagen. Capturing omni-range context for omnidirectional segmentation. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pages 1376-1386, 2021.","title":"Capturing omni-range context for omnidirectional segmentation","authors":"Yang","year":"2021","venue":"Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition","doi":null,"url":null,"internal_url":null},{"position":24,"raw":"[Yang et al., 2021b] Xue Yang, Junchi Yan, Qi Ming, Wen- tao Wang, Xiaopeng Zhang, and Qi Tian. Rethinking ro- tated object detection with gaussian wasserstein distance loss. In International Conference on Machine Learning, pages 11830-11841. PMLR, 2021.","title":"Rethinking rotated object detection with gaussian wasserstein distance loss","authors":"Yang","year":"2021","venue":"International Conference on Machine Learning","doi":null,"url":null,"internal_url":null},{"position":25,"raw":"[Yang et al., 2021c] Xue Yang, Xiaojiang Yang, Jirui Yang, Qi Ming, Wentao Wang, Qi Tian, and Junchi Yan. Learn- ing high-precision bounding box for rotated object detec- tion via kullback-leibler divergence. Advances in Neural Information Processing Systems, 34:18381-18394, 2021.","title":"Learning high-precision bounding box for rotated object detection via kullback-leibler divergence","authors":"Yang","year":"2021","venue":"Advances in Neural Information Processing Systems","doi":null,"url":null,"internal_url":null},{"position":26,"raw":"[Yang et al., 2022a] Xue Yang, Gefan Zhang, Xiaojiang Yang, Yue Zhou, Wentao Wang, Jin Tang, Tao He, and Junchi Yan. Detecting rotated objects as gaussian distri- butions and its 3-d generalization. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022.","title":"Detecting rotated objects as gaussian distributions and its 3-d generalization","authors":"Yang","year":"2022","venue":"IEEE Transactions on Pattern Analysis and Machine Intelligence","doi":null,"url":null,"internal_url":null},{"position":27,"raw":"[Yang et al., 2022b] Xue Yang, Yue Zhou, Gefan Zhang, Ji- tui Yang, Wentao Wang, Junchi Yan, Xiaopeng Zhang, and Qi Tian. The kfiou loss for rotated object detection. arXiv preprint arXiv:2201.12558, 2022.","title":"The kfiou loss for rotated object detection","authors":"Yang","year":"2022","venue":null,"doi":null,"url":null,"internal_url":null},{"position":28,"raw":"[Yu et al., 2016] Jiahui Yu, Yuning Jiang, Zhangyang Wang, Zhimin Cao, and Thomas Huang. Unitbox: An advanced object detection network. In Proceedings of the 24th ACM international conference on Multimedia, pages 516-520, 2016.","title":"Unitbox: An advanced object detection network","authors":"Jiahui Yu, Yuning Jiang, Zhangyang Wang, Zhimin Cao, Thomas Huang","year":"2016","venue":"Proceedings of the 24th ACM international conference on Multimedia","doi":null,"url":null,"internal_url":null},{"position":29,"raw":"[Zhang et al., 2020] Shifeng Zhang, Cheng Chi, Zhen Lei, and Stan Z Li. Refineface: Refinement neural network for high performance face detection. IEEE transactions on pattern analysis and machine intelligence, 43(11):4008- 4020, 2020.","title":"Refineface: Refinement neural network for high performance face detection","authors":"Shifeng Zhang, Cheng Chi, Zhen Lei, Stan Z Li","year":"2020","venue":"IEEE transactions on pattern analysis and machine intelligence","doi":null,"url":null,"internal_url":null},{"position":30,"raw":"[Zhang et al., 2021] Xue Zhang, Gene Cheung, Yao Zhao, Patrick Le Callet, Chunyu Lin, and Jack ZG Tan. Graph learning based head movement prediction for interactive 360 video streaming. IEEE Transactions on Image Pro- cessing, 30:4622-4636, 2021.","title":"Graph learning based head movement prediction for interactive 360 video streaming","authors":"Xue Zhang, Gene Cheung, Yao Zhao, Patrick Le Callet, Chunyu Lin, Jack Zg Tan","year":"2021","venue":"IEEE Transactions on Image Processing","doi":null,"url":null,"internal_url":null},{"position":31,"raw":"[Zhao et al., 2020] Pengyu Zhao, Ansheng You, Yuanxing Zhang, Jiaying Liu, Kaigui Bian, and Yunhai Tong. Spher- ical criteria for fast and accurate 360 object detection. In Proceedings of the AAAI Conference on Artificial Intelli- gence, volume 34, pages 12959-12966, 2020.","title":"Spherical criteria for fast and accurate 360 object detection","authors":"Pengyu Zhao, Ansheng You, Yuanxing Zhang, Jiaying Liu, Kaigui Bian, Yunhai Tong","year":"2020","venue":"Proceedings of the AAAI Conference on Artificial Intelligence","doi":null,"url":null,"internal_url":null},{"position":32,"raw":"[Zheng et al., 2020] Zhaohui Zheng, Ping Wang, Wei Liu, Jinze Li, Rongguang Ye, and Dongwei Ren. Distance-iou loss: Faster and better learning for bounding box regres- sion. In Proceedings of the AAAI conference on artificial intelligence, volume 34, pages 12993-13000, 2020.","title":"Distance-iou loss: Faster and better learning for bounding box regression","authors":"Zhaohui Zheng, Ping Wang, Wei Liu, Jinze Li, Rongguang Ye, Dongwei Ren","year":"2020","venue":"Proceedings of the AAAI conference on artificial intelligence","doi":null,"url":null,"internal_url":null},{"position":33,"raw":"[Zheng et al., 2021] Zhaohui Zheng, Ping Wang, Dongwei Ren, Wei Liu, Rongguang Ye, Qinghua Hu, and Wang- meng Zuo. Enhancing geometric factors in model learning and inference for object detection and instance segmenta- tion. IEEE Transactions on Cybernetics, 2021.","title":"Enhancing geometric factors in model learning and inference for object detection and instance segmentation","authors":"Zhaohui Zheng, Ping Wang, Dongwei Ren, Wei Liu, Rongguang Ye, Qinghua Hu, Wangmeng Zuo","year":"2021","venue":"IEEE Transactions on Cybernetics","doi":null,"url":null,"internal_url":null},{"position":34,"raw":"[Zhou et al., 2019] Dingfu Zhou, Jin Fang, Xibin Song, Chenye Guan, Junbo Yin, Yuchao Dai, and Ruigang Yang. Iou loss for 2d/3d object detection. In 2019 International Conference on 3D Vision (3DV), pages 85-94. IEEE, 2019.","title":"Iou loss for 2d/3d object detection","authors":"Zhou","year":"2019","venue":"International Conference on 3D Vision (3DV)","doi":null,"url":null,"internal_url":null},{"position":35,"raw":"[Zhou et al., 2022] Yue Zhou, Xue Yang, Gefan Zhang, Ji- abao Wang, Yanyi Liu, Liping Hou, Xue Jiang, Xingzhao Liu, Junchi Yan, Chengqi Lyu, Wenwei Zhang, and Kai Chen. Mmrotate: A rotated object detection benchmark using pytorch. In Proceedings of the 30th ACM Interna- tional Conference on Multimedia, 2022.","title":"Mmrotate: A rotated object detection benchmark using pytorch","authors":"Yue Zhou, Xue Yang, Gefan Zhang, Jiabao Wang, Yanyi Liu, Liping Hou, Xue Jiang, Xingzhao Liu, Junchi Yan, Chengqi Lyu, Wenwei Zhang, Kai Chen","year":"2022","venue":"Proceedings of the 30th ACM International Conference on Multimedia","doi":null,"url":null,"internal_url":null}],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}