From Pixels to Semantics: Self-Supervised Video Object Segmentation With Multiperspective Feature Mining-Reference-Cited by-同舟云学术

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From Pixels to Semantics: Self-Supervised Video Object Segmentation With Multiperspective Feature Mining

Published:2022 Issue: Volume:31 Page:5801-5812
ISSN:1057-7149
Container-title:IEEE Transactions on Image Processing
language:
Short-container-title:IEEE Trans. on Image Process.

Author:

Li Ruoqi¹,Wang Yifan²^ORCID,Wang Lijun³,Lu Huchuan¹^ORCID,Wei Xiaopeng⁴^ORCID,Zhang Qiang⁴^ORCID

Affiliation:

1. School of Information and Communication Engineering, Dalian University of Technology, Dalian, China

2. School of Innovation and Entrepreneurship, Dalian University of Technology, Dalian, China

3. School of Artificial Intelligence, Dalian University of Technology, Dalian, China

4. School of Computer Science and Technology, Dalian University of Technology, Dalian, China

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Graphics and Computer-Aided Design,Software

Link

http://xplorestaging.ieee.org/ielx7/83/9626658/09875116.pdf?arnumber=9875116

Reference67 articles.

1. Show, attend and tell: Neural image caption generation with visual attention;xu;Proc Int Conf Mach Learn,2015

2. Look and Think Twice: Capturing Top-Down Visual Attention with Feedback Convolutional Neural Networks

3. SCNet: Learning Semantic Correspondence

4. Do convnets learn correspondence?;long;Proc Conf Neural Inf Process Syst,2014

5. Emerging Properties in Self-Supervised Vision Transformers

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