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20232026
most citedAdaptive Integration of Partial Label Learning and Negative Learning for Enhanced Noisy Label Learning

3 citations · 5 across the 13 of their papers we have counts for

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Showing 2024Show all

5 papers · 1 filter

cs.MM2024

Relating CNN-Transformer Fusion Network for Change Detection

Yuhao Gao, Gensheng Pei, Mengmeng Sheng +3

While deep learning, particularly convolutional neural networks (CNNs), has revolutionized remote sensing (RS) change detection (CD), existing approaches often miss crucial feature…

cs.CV2024

Foster Adaptivity and Balance in Learning with Noisy Labels

Mengmeng Sheng, Zeren Sun, Tao Chen +3

Label noise is ubiquitous in real-world scenarios, posing a practical challenge to supervised models due to its effect in hurting the generalization performance of deep neural netw…

cs.CV2024★ 1 cited

Knowledge Transfer with Simulated Inter-Image Erasing for Weakly Supervised Semantic Segmentation

Tao Chen, XiRuo Jiang, Gensheng Pei +3

Though adversarial erasing has prevailed in weakly supervised semantic segmentation to help activate integral object regions, existing approaches still suffer from the dilemma of u…

cs.CV2024

VideoMAC: Video Masked Autoencoders Meet ConvNets

Gensheng Pei, Tao Chen, Xiruo Jiang +3

Recently, the advancement of self-supervised learning techniques, like masked autoencoders (MAE), has greatly influenced visual representation learning for images and videos. Never…

cs.CV2024

Spatial Structure Constraints for Weakly Supervised Semantic Segmentation

Tao Chen, Yazhou Yao, Xingguo Huang +3

The image-level label has prevailed in weakly supervised semantic segmentation tasks due to its easy availability. Since image-level labels can only indicate the existence or absen…