Multi-scale Deep Feature Transfer for Automatic Video Object Segmentation
Author:
Funder
The Natural Science Foundation of Hebei Province
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Computer Networks and Communications,General Neuroscience,Software
Link
https://link.springer.com/content/pdf/10.1007/s11063-023-11395-x.pdf
Reference90 articles.
1. Chen X, Li Z, Yuan Y, Yu G, Shen J, Qi D (2020) State-aware tracker for real-time video object segmentation. In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition, pp 9384–9393
2. Huang X, Xu J, Tai Y.-W, Tang C.-K (2020) Fast video object segmentation with temporal aggregation network and dynamic template matching. In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition, pp 8879–8889
3. Wang Y, Xu Z, Wang X, Shen C, Cheng B, Shen H, Xia H (2021) End-to-end video instance segmentation with transformers. In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition, pp 8741–8750
4. Liu J, Dai H.-N, Zhao G, Li B, Zhang T (2022) TMVOS: triplet matching for efficient video object segmentation. Signal Process Image Commun 107
5. Maddern W, Pascoe G, Linegar C, Newman P (2017) 1 year, 1000 km: The oxford robotcar dataset. Int J Robot Res 36(1):3–15
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