Look Before You Match: Instance Understanding Matters in Video Object Segmentation

Author:

Wang Junke1,Chen Dongdong2,Wu Zuxuan1,Luo Chong3,Tang Chuanxin3,Dai Xiyang2,Zhao Yucheng3,Xie Yujia2,Yuan Lu2,Jiang Yu-Gang1

Affiliation:

1. School of CS, Fudan University,Shanghai Key Lab of Intell. Info. Processing

2. Microsoft Cloud + AI

3. Microsoft Research Asia

Funder

NSFC

Publisher

IEEE

Reference76 articles.

1. XMem: Long-term video object segmentation with an atkinson-shiffrin memory model;ho;In ECCV,0

2. FEELVOS: Fast End-To-End Embedding Learning for Video Object Segmentation

3. Cascadepsp: Toward class-agnostic and very high-resolution segmentation via global and local refinement;ho;In CVPR,0

4. Video Segmentation via Object Flow

5. Rethinking space-time networks with improved memory coverage for efficient video object segmentation;ho;NeurIPS,0

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1. Scalable Video Object Segmentation With Identification Mechanism;IEEE Transactions on Pattern Analysis and Machine Intelligence;2024-09

2. Learning effective feature representation for video object segmentation via memory;Knowledge-Based Systems;2024-09

3. Video object segmentation by multi-scale attention using bidirectional strategy;Image and Vision Computing;2024-08

4. ISAR: A Benchmark for Single- and Few-Shot Object Instance Segmentation and Re-Identification;2024 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV);2024-01-03

5. DeVOS: Flow-Guided Deformable Transformer for Video Object Segmentation;2024 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV);2024-01-03

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