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EquiAV: Leveraging Equivariance for Audio-Visual Contrastive Learning
Recent advancements in self-supervised audio-visual representation learning have demonstrated its potential to capture rich and comprehensive representations.
UniCLIP: Unified Framework for Contrastive Language-Image Pre-training
Pre-training vision-language models with contrastive objectives has shown promising results that are both scalable to large uncurated datasets and transferable to many downstream applications.
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