Adaptive Guidance and Attention-Refined Network for Fast Video Object Segmentation
Author:
Funder
National Natural Science Foundation of China
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/s11063-023-11257-6.pdf
Reference57 articles.
1. Bao L, Wu B, Liu w (2018) CNN in MRF: video object segmentation via inference in a CNN-based higher-order spatio-temporal MRF’. In: IEEE conference on computer vision and pattern recognition (CVPR), pp 5977–5986
2. Caelles S et al (2017) One-shot video object segmentation. In: IEEE conference on computer vision and pattern recognition (CVPR), pp 5320–5329
3. Chen X et al (2020) State-aware tracker for real-time video object segmentation. In: IEEE conference on computer vision and pattern recognition (CVPR), pp 9384–9393
4. Cheng J et al (2018) Fast and accurate online video object segmentation via tracking parts. In: IEEE conference on computer vision and pattern recognition (CVPR), pp 7415–7424
5. Ci H, Wang C, Wang Y (2018) Video object segmentation by learning location-sensitive embeddings. In: European conference on computer vision (ECCV). Springer, pp 524–539
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