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LaT: Latent Translation with Cycle-Consistency for Video-Text Retrieval
To overcome the above issue, we present a novel mechanism for learning the translation relationship from a source modality space $\mathcal{S}$ to a target modality space $\mathcal{T}$ without the need for a joint latent space, which bridges the gap between visual and textual domains.
Ranked #11 on
Zero-Shot Video Retrieval
on MSVD
Weakly Supervised Image Classification Through Noise Regularization
Weakly supervised learning is an essential problem in computer vision tasks, such as image classification, object recognition, etc., because it is expected to work in the scenarios where a large dataset with clean labels is not available.
