Segment and Track Anything

Perazzi, F., Pont-Tuset, J., McWilliams, B., Van Gool, L., Gross, M., Sorkine-Hornung, A.: A benchmark dataset and evaluation methodology for video object segmentation. In: CVPR. pp. 724–732 (2016)

2016

Earlier work this paper cites.

Pont-Tuset, J., Perazzi, F., Caelles, S., Arbeláez, P., Sorkine-Hornung, A., Van Gool, L.: The 2017 davis challenge on video object segmentation. arXiv preprint arXiv:1704.00675 (2017)

Original

2017

Earlier work this paper cites.

Wang, W., Shen, J., Yang, R., Porikli, F.: Saliency-aware video object segmentation. TPAMI 40

2017

Earlier work this paper cites.

Lu, X., Wang, W., Ma, C., Shen, J., Shao, L., Porikli, F.: See more, know more: Unsupervised video object segmentation with co-attention siamese networks. In: CVPR. pp. 3623–3632 (2019)

2019

Earlier work this paper cites.

Wang, W., Lu, X., Shen, J., Crandall, D.J., Shao, L.: Zero-shot video object segmentation via attentive graph neural networks. In: ICCV. pp. 9236–9245 (2019)

2019

Earlier work this paper cites.

Wang, W., Song, H., Zhao, S., Shen, J., Zhao, S., Hoi, S.C., Ling, H.: Learning unsupervised video object segmentation through visual attention. In: CVPR. pp. 3064–3074 (2019)

2019

Earlier work this paper cites.

Lu, X., Wang, W., Danelljan, M., Zhou, T., Shen, J., Van Gool, L.: Video object segmentation with episodic graph memory networks. In: ECCV. pp. 661–679 (2020)

2020

Earlier work this paper cites.

Yang, Z., Wei, Y., Yang, Y.: Collaborative video object segmentation by foreground-background integration. In: ECCV. pp. 332–348. Springer (2020)

2020

Earlier work this paper cites.

Cheng, H.K., Tai, Y.W., Tang, C.K.: Modular interactive video object segmentation: Interaction-to-mask, propagation and difference-aware fusion. In: CVPR (2021)

2021

Cited alongside, same era.

Cheng, H.K., Tai, Y.W., Tang, C.K.: Rethinking space-time networks with improved memory coverage for efficient video object segmentation. In: NeurIPS (2021)

2021

Cited alongside, same era.

Yang, Z., Wei, Y., Yang, Y.: Associating objects with transformers for video object segmentation. In: NeurIPS (2021)

2021

Cited alongside, same era.

Yang, Z., Wei, Y., Yang, Y.: Collaborative video object segmentation by multi-scale foreground-background integration. TPAMI pp. 1–1 (2021). https://doi.org/10.1109/TPAMI.2021.3081597

2021

Cited alongside, same era.

Yang, Z., Zhang, J., Wang, W., Han, W., Yu, Y., Li, Y., Wang, J., Wei, Y., Sun, Y., Yang, Y.: Towards multi-object association from foreground-background integration. In: CVPR Workshops. vol. 2, p. 1 (2021)

Zhang, H., Li, F., Liu, S., Zhang, L., Su, H., Zhu, J., Ni, L.M., Shum, H.Y.: Dino: Detr with improved denoising anchor boxes for end-to-end object detection. arXiv preprint arXiv:2203.03605 (2022)

Original

2022

Later among the works it cites.

Zhou, T., Porikli, F., Crandall, D.J., Van Gool, L., Wang, W.: A survey on deep learning technique for video segmentation. TPAMI (2022)

Original

2022

Later among the works it cites.

Cho, S., Lee, M., Lee, S., Park, C., Kim, D., Lee, S.: Treating motion as option to reduce motion dependency in unsupervised video object segmentation. In: WACV. pp. 5140–5149 (2023)

2023

Closest in time.

Kirillov, A., Mintun, E., Ravi, N., Mao, H., Rolland, C., Gustafson, L., Xiao, T., Whitehead, S., Berg, A.C., Lo, W.Y., Dollár, P., Girshick, R.: Segment anything (2023)

2023

Closest in time.