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We present a new, embarrassingly simple approach to instance segmentation in images.
Lin, T., Maire, M., Belongie, S.J., Hays, J., Perona, P., Ramanan, D., Dollár, P., Zitnick, C.L.: Microsoft COCO: common objects in context. In: Proc. Eur. Conf. Comp. Vis. (2014)
2014
Earlier work this paper cites.
Long, J., Shelhamer, E., Darrell, T.: Fully convolutional networks for semantic segmentation. In: Proc. IEEE Conf. Comp. Vis. Patt. Recogn. (2015)
2015
Earlier work this paper cites.
Pinheiro, P.H.O., Collobert, R., Dollár, P.: Learning to segment object candidates. In: Proc. Advances in Neural Inf. Process. Syst. (2015)
2015
Earlier work this paper cites.
Ren, S., He, K., Girshick, R.B., Sun, J.: Faster R-CNN: towards real-time object detection with region proposal networks. In: Proc. Advances in Neural Inf. Process. Syst. (2015)
2015
Earlier work this paper cites.
Dai, J., He, K., Sun, J.: Instance-aware semantic segmentation via multi-task network cascades. In: Proc. IEEE Conf. Comp. Vis. Patt. Recogn. (2016)
2016
Earlier work this paper cites.
Milletari, F., Navab, N., Ahmadi, S.A.: V-net: Fully convolutional neural networks for volumetric medical image segmentation. In: Proc. Int. Conf. 3D Vision (2016)
2016
Earlier work this paper cites.
Dai, J., Qi, H., Xiong, Y., Li, Y., Zhang, G., Hu, H., Wei, Y.: Deformable convolutional networks. In: Proc. IEEE Int. Conf. Comp. Vis. (2017)
2017
Earlier work this paper cites.
2017
Earlier work this paper cites.
He, K., Gkioxari, G., Dollár, P., Girshick, R.B.: Mask R-CNN. In: Proc. IEEE Int. Conf. Comp. Vis. (2017)
2017
Earlier work this paper cites.
Li, Y., Qi, H., Dai, J., Ji, X., Wei, Y.: Fully convolutional instance-aware semantic segmentation. In: Proc. IEEE Conf. Comp. Vis. Patt. Recogn. (2017)
2017
Earlier work this paper cites.
Lin, T., Dollár, P., Girshick, R.B., He, K., Hariharan, B., Belongie, S.J.: Feature pyramid networks for object detection. In: Proc. IEEE Conf. Comp. Vis. Patt. Recogn. (2017)
2017
Cited alongside, same era.
Lin, T.Y., Goyal, P., Girshick, R., He, K., Dollár, P.: Focal loss for dense object detection. In: Proc. IEEE Int. Conf. Comp. Vis. (2017)
2017
Cited alongside, same era.
Liu, S., Jia, J., Fidler, S., Urtasun, R.: Sequential grouping networks for instance segmentation. In: Proc. IEEE Int. Conf. Comp. Vis. (2017)
2017
Cited alongside, same era.
Newell, A., Huang, Z., Deng, J.: Associative embedding: End-to-end learning for joint detection and grouping. In: Proc. Advances in Neural Inf. Process. Syst. (2017)
2017
Cited alongside, same era.
Chen, L.C., Hermans, A., Papandreou, G., Schroff, F., Wang, P., Adam, H.: Masklab: Instance segmentation by refining object detection with semantic and direction features. In: Proc. IEEE Conf. Comp. Vis. Patt. Recogn. (2018)
Chen, K., Pang, J., Wang, J., Xiong, Y., Li, X., Sun, S., Feng, W., Liu, Z., Shi, J., Ouyang, W., et al.: Hybrid task cascade for instance segmentation. In: Proc. IEEE Conf. Comp. Vis. Patt. Recogn. (2019)
2019
Closest in time.
Chen, X., Girshick, R., He, K., Dollar, P.: Tensormask: A foundation for dense object segmentation. In: Proc. IEEE Int. Conf. Comp. Vis. (2019)
2019
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Gao, N., Shan, Y., Wang, Y., Zhao, X., Yu, Y., Yang, M., Huang, K.: Ssap: Single-shot instance segmentation with affinity pyramid. In: Proc. IEEE Int. Conf. Comp. Vis. (2019)
2019
Closest in time.
Huang, Z., Huang, L., Gong, Y., Huang, C., Wang, X.: Mask scoring R-CNN. In: Proc. IEEE Conf. Comp. Vis. Patt. Recogn. (2019)
2019
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Sofiiuk, K., Barinova, O., Konushin, A.: Adaptis: Adaptive instance selection network. In: Proc. IEEE Int. Conf. Comp. Vis. (2019)
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2018
Cited alongside, same era.
Liu, R., Lehman, J., Molino, P., Such, F.P., Frank, E., Sergeev, A., Yosinski, J.: An intriguing failing of convolutional neural networks and the coordconv solution. In: Proc. Advances in Neural Inf. Process. Syst. (2018)
2018
Cited alongside, same era.
Liu, S., Qi, L., Qin, H., Shi, J., Jia, J.: Path aggregation network for instance segmentation. In: Proc. IEEE Conf. Comp. Vis. Patt. Recogn. (2018)
2018
Cited alongside, same era.
Novotný, D., Albanie, S., Larlus, D., Vedaldi, A.: Semi-convolutional operators for instance segmentation. In: Proc. Eur. Conf. Comp. Vis. (2018)
2018
Cited alongside, same era.
Bolya, D., Zhou, C., Xiao, F., Lee, Y.J.: YOLACT: Real-time instance segmentation. In: Proc. IEEE Int. Conf. Comp. Vis. (2019)
2019
Cited alongside, same era.
2019
Closest in time.
Tian, Z., Shen, C., Chen, H., He, T.: FCOS: Fully convolutional one-stage object detection. In: Proc. IEEE Int. Conf. Comp. Vis. (2019)
2019
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Islam*, M.A., Jia*, S., Bruce, N.D.B.: How much position information do convolutional neural networks encode? In: Proc. Int. Conf. Learn. Representations (2020)
2020
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Kong, T., Sun, F., Liu, H., Jiang, Y., Li, L., Shi, J.: Foveabox: Beyond anchor-based object detector. IEEE Trans. Image Process. pp. 7389–7398 (2020)
2020
Closest in time.