2026
HVD: HUMAN VISION-DRIVEN VIDEO REPRESENTATION LEARNING FOR TEXT-VIDEO RETRIEVAL
ICASSP 2026poster
The success of CLIP has driven substantial progress in text-video retrieval. However, current methods often suffer from "blind" feature interaction, where the model struggles to discern key visual information from background noise due to the sparsity of textual queries. To bridge this gap, we draw i…