Fine-grained recognition via submodular optimization regulated progressive training-Reference-Cited by-同舟云学术

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Fine-grained recognition via submodular optimization regulated progressive training

Published:2024-12 Issue: Volume:156 Page:110849
ISSN:0031-3203
Container-title:Pattern Recognition
language:en
Short-container-title:Pattern Recognition

Author:

Kang Bin^ORCID,Du Songlin^ORCID,Liang Dong,Wu Fan,Li Xin^ORCID

Funder

National Natural Science Foundation of China

China Postdoctoral Science Foundation

Publisher

Elsevier BV

Reference50 articles.

1. Content-aware rectified activation for zero-shot fine-grained image retrieval;Wang;IEEE Trans. Pattern Anal. Mach. Intell.,2024

2. S. Joung, S. Kim, M. Kim, I.-J. Kim, K. Sohn, Learning canonical 3d object representation for fine-grained recognition, in: Proceedings of the IEEE/CVF International Conference on Computer Vision, 2021, pp. 1035–1045.

3. Correlation-guided semantic consistency network for visible-infrared person re-identification;Li;IEEE Trans. Circuits Syst. Video Technol.,2023

4. Knowledge-embedded representation learning for fine-grained image recognition;Chen,2018

5. A survey on curriculum learning;Wang;IEEE Trans. Pattern Anal. Mach. Intell.,2021

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