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Single-stage instance segmentation approaches have recently gained popularity due to their speed and simplicity, but are still lagging behind in accuracy, compared to two-stage methods.
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Pinheiro, P.O., Lin, T.Y., Collobert, R., Dollár, P.: Learning to refine object segments. Proc. European Conf. Computer Vision (2016)
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Chen, L.C., Papandreou, G., Kokkinos, I., Murphy, K., Yuille, A.L.: Deeplab: Semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected crfs. IEEE Trans. Pattern Analysis and Machine Intelligence 40
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Dai, J., Qi, H., Xiong, Y., Li, Y., Zhang, G., Hu, H., Wei, Y.: Deformable convolutional networks. Proc. IEEE International Conf. Computer Vision (2017)
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Kirillov, A., Levinkov, E., Andres, B., Savchynskyy, B., Rother, C.: Instancecut: from edges to instances with multicut. Proc. IEEE Conf. Computer Vision and Pattern Recognition (2017)
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Li, Y., Qi, H., Dai, J., Ji, X., Wei, Y.: Fully convolutional instance-aware semantic segmentation. Proc. IEEE Conf. Computer Vision and Pattern Recognition (2017)
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Liu, S., Qi, L., Qin, H., Shi, J., Jia, J.: Path aggregation network for instance segmentation. Proc. IEEE Conf. Computer Vision and Pattern Recognition (2018)
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Yang, L., Wang, Y., Xiong, X., Yang, J., Katsaggelos, A.K.: Efficient video object segmentation via network modulation. Proc. IEEE Conf. Computer Vision and Pattern Recognition (2018)
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Bolya, D., Zhou, C., Xiao, F., Lee, Y.J.: Yolact: Real-time instance segmentation. Proc. IEEE International Conf. Computer Vision (2019)
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Cao, J., Pang, Y., Han, J., Li, X.: Hierarchical shot detector. Proc. IEEE International Conference on Computer Vision (2019)
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Cao, J., Pang, Y., Li, X.: Triply supervised decoder networks for joint detection and segmentation. Proc. IEEE Conf. Computer Vision and Pattern Recognition (2019)
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Xu, W., Wang, H., Qi, F., Lu, C.: Explicit shape encoding for real-time instance segmentation. Proc. IEEE International Conf. Computer Vision (2019)
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Yang, Z., Liu, S., Hu, H., Wang, L., Lin, S.: Reppoints: Point set representation for object detection. Proc. IEEE International Conf. Computer Vision (2019)
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Ye, M., Zhang, X., Yuen, P.C., Chang, S.F.: Unsupervised embedding learning via invariant and spreading instance feature. In: Proc. IEEE Conf. Computer Vision and Pattern Recognition (2019)
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2019
Cited alongside, same era.
Chen, K., Pang, J., Wang, J., Xiong, Y., Li, X., Sun, S., Feng, W., Liu, Z., Shi, J., Ouyang, W., Loy, C.C., Lin, D.: Hybrid task cascade for instance segmentation. Proc. IEEE Conf. Computer Vision and Pattern Recognition (2019)
2019
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Chen, X., Girshick, R., He, K., Dollár, P.: Tensormask: A foundation for dense object segmentation. Proc. IEEE International Conf. Computer Vision (2019)
2019
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Cholakkal, H., Sun, G., Khan, F.S., Shao, L.: Object counting and instance segmentation with image-level supervision. Proc. IEEE Conf. Computer Vision and Pattern Recognition (2019)
2019
Cited alongside, same era.
Fang, H.S., Sun, J., Wang, R., Gou, M., Li, Y.L., Lu, C.: Instaboost: Boosting instance segmentation via probability map guided copy-pasting. Proc. IEEE International Conf. Computer Vision (2019)
2019
Cited alongside, same era.
2019
Cited alongside, same era.
Gao, N., Shan, Y., Wang, Y., Zhao, X., Yu, Y., Yang, M., Huang, K.: Ssap: Single-shot instance segmentation with affinity pyramid. Proc. IEEE International Conf. Computer Vision (2019)
2019
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Huang, Z., Huang, L., Gong, Y., Huang, C., Wang, X.: Mask scoring r-cnn. Proc. IEEE Conf. Computer Vision and Pattern Recognition (2019)
2019
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2019
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Zhou, X., Zhuo, J., Krahenbuhl, P.: Bottom-up object detection by grouping extreme and center points. Proc. IEEE Conf. Computer Vision and Pattern Recognition (2019)
2019
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Zhu, X., Hu, H., Lin, S., Dai, J.: Deformable convnets v2: More deformable, better results. Proc. IEEE Conf. Computer Vision and Pattern Recognition (2019)
2019
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2020
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Cao, J., Cholakkal, H., Anwer, R.M., Khan, F.S., Pang, Y., Shao, L.: D2det: Towards high quality object detection and instance segmentation. Proc. IEEE Conf. Computer Vision and Pattern Recognition (2020)
2020
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2020
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2020
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Peng, S., Jiang, W., Pi, H., Li, X., Bao, H., Zhou, X.: Deep snake for real-time instance segmentation. Proc. IEEE Conf. Computer Vision and Pattern Recognition (2020)
2020
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Sun, G., Wang, B., Dai, J., Gool, L.V.: Mining cross-image semantics for weakly supervised semantic segmentation. Proc. European Conf. Computer Vision (2020)
2020
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Wang, S., Gong, Y., Xing, J., Huang, L., Huang, C., Hu, W.: Rdsnet: A new deep architecture for reciprocal object detection and instance segmentation. Proc. AAAI Conf. Artificial Intelligence (2020)
2020
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2020
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Wu, J., Zhou, C., Yang, M., Zhang, Q., Li, Y., Yuan, J.: Temporal-context enhanced detection of heavily occluded pedestrians. Proc. IEEE Conference on Computer Vision and Pattern Recognition (2020)
2020
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Yang, Z., Xu, Y., Xue, H., Zhang, Z., Urtasun, R., Wang, L., Lin, S., Hu, H.: Reppoints: Point set representation for object detection. Proc. European Conf. Computer Vision (2020)
2020
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