Background-Aware Classification Activation Map for Weakly Supervised Object Localization-Reference-Cited by-同舟云学术

Background-Aware Classification Activation Map for Weakly Supervised Object Localization

Published:2023-12 Issue:12 Volume:45 Page:14175-14191
ISSN:0162-8828
Container-title:IEEE Transactions on Pattern Analysis and Machine Intelligence
language:
Short-container-title:IEEE Trans. Pattern Anal. Mach. Intell.

Author:

Zhu Lei¹^ORCID,She Qi²^ORCID,Chen Qian¹^ORCID,Meng Xiangxi³^ORCID,Geng Mufeng¹^ORCID,Jin Lujia¹^ORCID,Zhang Yibao³^ORCID,Ren Qiushi¹^ORCID,Lu Yanye¹^ORCID

Affiliation:

1. Institute of Medical Technology, Peking University Health Science Center, Peking University, Beijing, China

2. ByteDance AI Lab, ByteDance, Beijing, China

3. Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Peking University Cancer Hospital & Institute, Beijing, China

Funder

National Natural Science Foundation of China

Beijing Natural Science Foundation

Peking University Medicine Sailing Program for Young Scholars’ Scientific & Technological Innovation

Shenzhen Science and Technology Program, China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Applied Mathematics,Artificial Intelligence,Computational Theory and Mathematics,Computer Vision and Pattern Recognition,Software

Link

http://xplorestaging.ieee.org/ielx7/34/10308548/10234096.pdf?arnumber=10234096

Reference67 articles.

1. Weakly supervised instance segmentation using the bounding box tightness prior;Hsu

2. Counterfactual contrastive learning for weakly-supervised vision-language grounding;Zhang

3. Self-Supervised Equivariant Attention Mechanism for Weakly Supervised Semantic Segmentation

4. Learning Deep Features for Discriminative Localization

5. Weakly-Supervised Learning of Visual Relations

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