[2] [2] Chiu H K, Li J, Ambru R, et al. Probabilistic 3D multi-modal, multi-object tracking for autonomous driving[C]//Proceedings of 2021 IEEE International Conference on Robotics and Automation, 2021: 14227–14233.

[9] [9] Muller N, Wong Y S, Mitra N J, et al. Seeing behind objects for 3D multi-object tracking in RGB-D sequences[C]//Proceedings of 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2021: 6067–6076.

[10] [10] He J W, Huang Z H, Wang N Y, et al. Learnable graph matching: Incorporating graph partitioning with deep feature learning for multiple object tracking[C]//Proceedings of 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2021: 5295–5305.

[11] [11] Zhan X H, Pan X G, Dai B, et al. Self-supervised scene de-occlusion[C]//Proceedings of 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020: 3783–3791.

[13] [13] Luo C X, Yang X D, Yuille A. Self-supervised pillar motion learning for autonomous driving[C]//Proceedings of 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2021: 3182–3191.

[14] [14] Han T D, Xie W D, Zisserman A. Video representation learning by dense predictive coding[C]//Proceedings of 2019 IEEE/CVF International Conference on Computer Vision Workshop, 2019: 1483–1492.

[15] [15] Wang Q, Zheng Y, Pan P, et al. Multiple object tracking with correlation learning[C]//Proceedings of 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2021: 3875–3885.

[16] [16] Tian Z, Shen C H, Chen H, et al. FCOS: fully convolutional one-stage object detection[C]//Proceedings of 2019 IEEE/CVF International Conference on Computer Vision, 2019: 9626–9635.

[17] [17] Ying H, Huang Z J, Liu S, et al. EmbedMask: embedding coupling for one-stage instance segmentation[Z]. arXiv: 1912.01954, 2019. https://doi.org/10.48550/arXiv.1912.01954.

[19] [19] He K M, Gkioxari G, Dollár P, et al. Mask R-CNN[C]//Proceedings of 2017 IEEE International Conference on Computer Vision, 2017: 2980–2988.

[20] [20] Kim C, Li F X, Rehg J M. Multi-object tracking with neural gating using bilinear LSTM[C]//Proceedings of the 15th European Conference on Computer Vision, 2018: 208–224.

[21] [21] Bolya D, Zhou C, Xiao F Y, et al. YOLACT: real-time instance segmentation[C]//Proceedings of 2019 IEEE/CVF International Conference on Computer Vision, 2019: 9156–9165.

[22] [22] Redmon J, Farhadi A. Yolov3: an incremental improvement[Z]. arXiv: 1804.02767, 2018. https://doi.org/10.48550/arXiv.1804.02767.

[23] [23] Ren S Q, He K M, Girshick R, et al. Faster R-CNN: towards real-time object detection with region proposal networks[C]//Proceedings of the 28th International Conference on Neural Information Processing Systems, 2015: 91–99.

[24] [24] Tu Z G, Cao J, Li Y K, et al. MSR-CNN: applying motion salient region based descriptors for action recognition[C]//Proceedings of the 2016 23rd International Conference on Pattern Recognition, 2016: 3524–3529.

[25] [25] Yang L J, Fan Y C, Xu N. Video instance segmentation[C]//Proceedings of 2019 IEEE/CVF International Conference on Computer Vision, 2019: 5187–5196.

[26] [26] Voigtlaender P, Krause M, Osep A, et al. MOTS: multi-object tracking and segmentation[C]//Proceedings of 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2019: 7934–7943.