4 citations · 13 across the 8 of their papers we have counts for
3 papers · 1 filter
Disentangled Noisy Correspondence Learning
Zhuohang Dang, Minnan Luo, Jihong Wang +6
Cross-modal retrieval is crucial in understanding latent correspondences across modalities. However, existing methods implicitly assume well-matched training data, which is impract…
Disentangled Representation Learning with Transmitted Information Bottleneck
Zhuohang Dang, Minnan Luo, Chengyou Jia +4
Encoding only the task-related information from the raw data, \ie, disentangled representation learning, can greatly contribute to the robustness and generalizability of models. Al…
Disentangled Generation with Information Bottleneck for Few-Shot Learning
Zhuohang Dang, Jihong Wang, Minnan Luo +3
Few-shot learning (FSL), which aims to classify unseen classes with few samples, is challenging due to data scarcity. Although various generative methods have been explored for FSL…