Mask-aided Object Detection

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Help generate proposal:

Help generate proposal:

  1. Combine semantic mask with feature map (e.g., concatenation, summation) to help predict bounding boxes: [1] [2] [3]

  2. Generate proposals from semantic mask: [4]

Help select proposal:

  1. Assign weights to proposals based on semantic mask: [5]

  2. Use semantic mask surrounding each proposal as auxilary feature: [6]

Reference

[1] Yan Liu, Zhijie Zhang, Li Niu, Junjie Chen, Liqing Zhang, “Mixed Supervised Object Detection by Transferring Mask Prior and Semantic Similarity”, NeurIPS, 2021.

[2] Zitian Chen, Zhiqiang Shen, Jiahui Yu, Erik Learned-Miller: “Cross-Supervised Object Detection.” arXiv preprint arXiv:2006.15056 (2020)

[3] Zhao, Xiangyun, Shuang Liang, and Yichen Wei. “Pseudo mask augmented object detection.” CVPR, 2018.

[4] Diba, Ali, et al. “Weakly supervised cascaded convolutional networks.” CVPR, 2017.

[5] Li, Xiaoyan, et al. “Weakly supervised object detection with segmentation collaboration.” ICCV, 2019.

[6] Wei, Yunchao, et al. “Ts2c: Tight box mining with surrounding segmentation context for weakly supervised object detection.” ECCV, 2018.