SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory
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2411.11922
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18
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MM-Ego: Towards Building Egocentric Multimodal LLMs
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2410.07177
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Contrastive Localized Language-Image Pre-Training
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2206.05836
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Grounded Language-Image Pre-training
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Ferret: Refer and Ground Anything Anywhere at Any Granularity
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2310.07704
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From Scarcity to Efficiency: Improving CLIP Training via Visual-enriched Captions
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How Easy is It to Fool Your Multimodal LLMs? An Empirical Analysis on Deceptive Prompts
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2402.13220
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MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training
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2403.09611
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