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cs.CV2024
Free Performance Gain from Mixing Multiple Partially Labeled Samples in Multi-label Image Classification
Chak Fong Chong, Jielong Guo, Xu Yang +2
Multi-label image classification datasets are often partially labeled where many labels are missing, posing a significant challenge to training accurate deep classifiers. However,…
cs.CV2024
Category-wise Fine-Tuning: Resisting Incorrect Pseudo-Labels in Multi-Label Image Classification with Partial Labels
Chak Fong Chong, Xinyi Fang, Jielong Guo +4
Large-scale image datasets are often partially labeled, where only a few categories' labels are known for each image. Assigning pseudo-labels to unknown labels to gain additional t…