2 citations · 6 across the 6 of their papers we have counts for
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cs.CV2024
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…
cs.CV2024
A Unified Optimal Transport Framework for Cross-Modal Retrieval with Noisy Labels
Haochen Han, Minnan Luo, Huan Liu +1
Cross-modal retrieval (CMR) aims to establish interaction between different modalities, among which supervised CMR is emerging due to its flexibility in learning semantic category…
cs.CV2024★ 2 cited
Learning to Rematch Mismatched Pairs for Robust Cross-Modal Retrieval
Haochen Han, Qinghua Zheng, Guang Dai +2
Collecting well-matched multimedia datasets is crucial for training cross-modal retrieval models. However, in real-world scenarios, massive multimodal data are harvested from the I…