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Distilling Vision-Language Models on Millions of Videos
Paper • 2401.06129 • Published • 14 -
Koala: Key frame-conditioned long video-LLM
Paper • 2404.04346 • Published • 5 -
MA-LMM: Memory-Augmented Large Multimodal Model for Long-Term Video Understanding
Paper • 2404.05726 • Published • 20 -
OphNet: A Large-Scale Video Benchmark for Ophthalmic Surgical Workflow Understanding
Paper • 2406.07471 • Published
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Collections including paper arxiv:2404.04346
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PLLaVA : Parameter-free LLaVA Extension from Images to Videos for Video Dense Captioning
Paper • 2404.16994 • Published • 35 -
VideoMamba: State Space Model for Efficient Video Understanding
Paper • 2403.06977 • Published • 27 -
VideoAgent: Long-form Video Understanding with Large Language Model as Agent
Paper • 2403.10517 • Published • 31 -
Video Mamba Suite: State Space Model as a Versatile Alternative for Video Understanding
Paper • 2403.09626 • Published • 13
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VideoAgent: Long-form Video Understanding with Large Language Model as Agent
Paper • 2403.10517 • Published • 31 -
VideoAgent: A Memory-augmented Multimodal Agent for Video Understanding
Paper • 2403.11481 • Published • 11 -
VideoMamba: State Space Model for Efficient Video Understanding
Paper • 2403.06977 • Published • 27 -
MovieLLM: Enhancing Long Video Understanding with AI-Generated Movies
Paper • 2403.01422 • Published • 26
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EVA-CLIP-18B: Scaling CLIP to 18 Billion Parameters
Paper • 2402.04252 • Published • 25 -
Vision Superalignment: Weak-to-Strong Generalization for Vision Foundation Models
Paper • 2402.03749 • Published • 12 -
ScreenAI: A Vision-Language Model for UI and Infographics Understanding
Paper • 2402.04615 • Published • 36 -
EfficientViT-SAM: Accelerated Segment Anything Model Without Performance Loss
Paper • 2402.05008 • Published • 19