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Current object detection frameworks mainly rely on bounding box regression to localize objects.
1904
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Chen, K., Wang, J., Yang, S., Zhang, X., Xiong, Y., Loy, C.C., Lin, D.: Optimizing video object detection via a scale-time lattice. In: CVPR (2018)
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Huang, Q., Xiong, Y., Lin, D.: Unifying identification and context learning for person recognition. In: CVPR (2018)
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Jiang, B., Luo, R., Mao, J., Xiao, T., Jiang, Y.: Acquisition of localization confidence for accurate object detection. In: ECCV (2018)
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Lu, X., Li, B., Yue, Y., Li, Q., Yan, J.: Grid R-CNN. In: CVPR (2019)
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Kong, T., Sun, F., Tan, C., Liu, H., Huang, W.: Deep feature pyramid reconfiguration for object detection. In: ECCV (2018)
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Law, H., Deng, J.: CornerNet: Detecting objects as paired keypoints. In: ECCV (2018)
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Liu, S., Qi, L., Qin, H., Shi, J., Jia, J.: Path aggregation network for instance segmentation. In: CVPR (2018)
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Wu, Y., He, K.: Group normalization. In: ECCV (2018)
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Zhang, S., Wen, L., Bian, X., Lei, Z., Li, S.Z.: Single-shot refinement neural network for object detection. In: CVPR (2018)
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Chen, K., Pang, J., Wang, J., Xiong, Y., Li, X., Sun, S., Feng, W., Liu, Z., Shi, J., Ouyang, W., Change Loy, C., Lin, D.: Hybrid task cascade for instance segmentation. In: CVPR (2019)
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Shi, S., Wang, X., Li, H.: Pointrcnn: 3d object proposal generation and detection from point cloud. In: CVPR (2019)
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Yang, Z., Liu, S., Hu, H., Wang, L., Lin, S.: Reppoints: Point set representation for object detection. In: ICCV (2019)
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Zhang, W., Zhou, H., Sun, S., Wang, Z., Shi, J., Loy, C.C.: Robust multi-modality multi-object tracking. In: ICCV (2019)
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Zhao, Q., Sheng, T., Wang, Y., Tang, Z., Chen, Y., Cai, L., Ling, H.: M2Det: a single-shot object detector based on multi-level feature pyramid network. In: AAAI (2019)
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