VEDJE: Efficient Video-Text Retrieval via Feature Compression
October 11, 2026
VEDJE improves video-text retrieval by compressing sampled frame features into a reusable 12 KiB cache while using feature-change prediction as an auxiliary signal. It achieves 59.8 text-to-video R@1 on MSR-VTT using a fine-tuned VideoCLIP-XL backbone.
HOW THIS AFFECTS YOU
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builderYou can scale video retrieval systems by using compressed caches that preserve recall while significantly reducing per-video storage costs.