Video Object Segmentation via SAM 2: The 4th Solution for LSVOS Challenge VOS Track

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.

Caelles, S., Maninis, K.K., Pont-Tuset, J., Leal-Taixé, L., Cremers, D., Van Gool, L.: One-shot video object segmentation. In: CVPR. pp. 221–230 (2017)

2017

Earlier work this paper cites.

Voigtlaender, P., Leibe, B.: Online adaptation of convolutional neural networks for video object segmentation. arXiv preprint arXiv:1706.09364 (2017)

Original

2017

Earlier work this paper cites.

Xu, N., Yang, L., Fan, Y., Yue, D., Liang, Y., Yang, J., Huang, T.: Youtube-vos: A large-scale video object segmentation benchmark. arXiv preprint arXiv:1809.03327 (2018)

Original

2018

Earlier work this paper cites.

Oh, S.W., Lee, J.Y., Xu, N., Kim, S.J.: Video object segmentation using space-time memory networks. In: ICCV. pp. 9226–9235 (2019)

2019

Earlier work this paper cites.

Lu, X., Wang, W., Shen, J., Crandall, D., Luo, J.: Zero-shot video object segmentation with co-attention siamese networks. PAMI 44

2020

Earlier work this paper cites.

Robinson, A., Lawin, F.J., Danelljan, M., Khan, F.S., Felsberg, M.: Learning fast and robust target models for video object segmentation. In: CVPR. pp. 7406–7415 (2020)

2020

Earlier work this paper cites.

Seo, S., Lee, J.Y., Han, B.: Urvos: Unified referring video object segmentation network with a large-scale benchmark. In: ECCV. pp. 208–223. 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. pp. 5559–5568 (2021)

2021

Cited alongside, same era.

Lu, X., Wang, W., Shen, J., Crandall, D.J., Van Gool, L.: Segmenting objects from relational visual data. PAMI 44

2021

Cited alongside, same era.

Yang, Z., Wei, Y., Yang, Y.: Associating objects with transformers for video object segmentation. NeurIPS 34

2021

Cited alongside, same era.

Cheng, H.K., Schwing, A.G.: Xmem: Long-term video object segmentation with an atkinson-shiffrin memory model. In: ECCV. pp. 640–658. Springer (2022)

2022

Cited alongside, same era.

Petrík, V., Qureshi, M.N., Sivic, J., Tapaswi, M.: Learning object manipulation skills from video via approximate differentiable physics. In: IROS. pp. 7375–7382. IEEE (2022)

2022

Ding, H., Liu, C., He, S., Jiang, X., Torr, P.H., Bai, S.: Mose: A new dataset for video object segmentation in complex scenes. In: ICCV. pp. 20224–20234 (2023)

2023

Later among the works it cites.

Hong, L., Chen, W., Liu, Z., Zhang, W., Guo, P., Chen, Z., Zhang, W.: Lvos: A benchmark for long-term video object segmentation. In: ICCV. pp. 13480–13492 (2023)

2023

Later among the works it cites.

Kirillov, A., Mintun, E., Ravi, N., Mao, H., Rolland, C., Gustafson, L., Xiao, T., Whitehead, S., Berg, A.C., Lo, W.Y., et al.: Segment anything. In: ICCV. pp. 4015–4026 (2023)

2023

Later among the works it cites.

Cheng, H.K., Oh, S.W., Price, B., Lee, J.Y., Schwing, A.: Putting the object back into video object segmentation. In: CVPR. pp. 3151–3161 (2024)

2024

Closest in time.

Fang, H., Wu, P., Li, Y., Zhang, X., Lu, X.: Unified embedding alignment for open-vocabulary video instance segmentation. arXiv preprint arXiv:2407.07427 (2024)