Multi-grained Temporal Prototype Learning for Few-shot Video Object Segmentation-Reference-Cited by-同舟云学术

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Multi-grained Temporal Prototype Learning for Few-shot Video Object Segmentation

Published:2023-10-01 Issue: Volume:34 Page:18816-18825
ISSN:
Container-title:2023 IEEE/CVF International Conference on Computer Vision (ICCV)
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Author:

Liu Nian¹,Nan Kepan²,Zhao Wangbo³,Liu Yuanwei²,Yao Xiwen²,Khan Salman¹,Cholakkal Hisham¹,Anwer Rao Muhammad¹,Han Junwei²,Khan Fahad Shahbaz¹

Affiliation:

1. Mohamed bin Zayed University of Artificial Intelligence

2. Northwestern Polytechnical University

3. National University of Singapore

Funder

National Natural Science Foundation of China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10376473/10376477/10377253.pdf?arnumber=10377253

Reference33 articles.

1. Delving Deep into Many-to-many Attention for Few-shot Video Object Segmentation

2. DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs

3. Masked-attention Mask Transformer for Universal Image Segmentation

4. Perpixel classification is not all you need for semantic segmentation;Cheng

5. XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory Model

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. M-RRFS: A Memory-Based Robust Region Feature Synthesizer for Zero-Shot Object Detection;International Journal of Computer Vision;2024-05-22

2. Expandable-RCNN: toward high-efficiency incremental few-shot object detection;Frontiers in Artificial Intelligence;2024-04-23

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