ReWind: Understanding Long Videos with Instructed Learnable Memory

Understand

Vision-Language Models (VLMs) are crucial for applications requiring integrated understanding textual and visual information.

• However, existing VLMs struggle with long videos due to computational inefficiency, memory limitations, and difficulties in maintaining coherent understanding across extended sequences.
• To address these challenges, we introduce ReWind, a novel memory-based VLM designed for efficient long video understanding while preserving temporal fidelity.
• ReWind operates in a two-stage framework.