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EVA-CLIP-18B: Scaling CLIP to 18 Billion Parameters
Paper • 2402.04252 • Published • 26 -
Vision Superalignment: Weak-to-Strong Generalization for Vision Foundation Models
Paper • 2402.03749 • Published • 13 -
ScreenAI: A Vision-Language Model for UI and Infographics Understanding
Paper • 2402.04615 • Published • 43 -
EfficientViT-SAM: Accelerated Segment Anything Model Without Performance Loss
Paper • 2402.05008 • Published • 22
Collections
Discover the best community collections!
Collections including paper arxiv:2502.20321
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DocLLM: A layout-aware generative language model for multimodal document understanding
Paper • 2401.00908 • Published • 180 -
COSMO: COntrastive Streamlined MultimOdal Model with Interleaved Pre-Training
Paper • 2401.00849 • Published • 17 -
LLaVA-Plus: Learning to Use Tools for Creating Multimodal Agents
Paper • 2311.05437 • Published • 50 -
LLaVA-Interactive: An All-in-One Demo for Image Chat, Segmentation, Generation and Editing
Paper • 2311.00571 • Published • 41
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Pangea: A Fully Open Multilingual Multimodal LLM for 39 Languages
Paper • 2410.16153 • Published • 44 -
AutoTrain: No-code training for state-of-the-art models
Paper • 2410.15735 • Published • 59 -
The Curse of Multi-Modalities: Evaluating Hallucinations of Large Multimodal Models across Language, Visual, and Audio
Paper • 2410.12787 • Published • 31 -
LEOPARD : A Vision Language Model For Text-Rich Multi-Image Tasks
Paper • 2410.01744 • Published • 26
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Depth Anything V2
Paper • 2406.09414 • Published • 97 -
An Image is Worth More Than 16x16 Patches: Exploring Transformers on Individual Pixels
Paper • 2406.09415 • Published • 51 -
Physics3D: Learning Physical Properties of 3D Gaussians via Video Diffusion
Paper • 2406.04338 • Published • 38 -
SAM 2: Segment Anything in Images and Videos
Paper • 2408.00714 • Published • 113
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EfficientViT-SAM: Accelerated Segment Anything Model Without Performance Loss
Paper • 2402.05008 • Published • 22 -
PALO: A Polyglot Large Multimodal Model for 5B People
Paper • 2402.14818 • Published • 24 -
MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training
Paper • 2403.09611 • Published • 126 -
InternLM-XComposer2-4KHD: A Pioneering Large Vision-Language Model Handling Resolutions from 336 Pixels to 4K HD
Paper • 2404.06512 • Published • 30
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WorldDreamer: Towards General World Models for Video Generation via Predicting Masked Tokens
Paper • 2401.09985 • Published • 17 -
CustomVideo: Customizing Text-to-Video Generation with Multiple Subjects
Paper • 2401.09962 • Published • 9 -
Inflation with Diffusion: Efficient Temporal Adaptation for Text-to-Video Super-Resolution
Paper • 2401.10404 • Published • 10 -
ActAnywhere: Subject-Aware Video Background Generation
Paper • 2401.10822 • Published • 13
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Compose and Conquer: Diffusion-Based 3D Depth Aware Composable Image Synthesis
Paper • 2401.09048 • Published • 10 -
Improving fine-grained understanding in image-text pre-training
Paper • 2401.09865 • Published • 17 -
Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data
Paper • 2401.10891 • Published • 60 -
Scaling Up to Excellence: Practicing Model Scaling for Photo-Realistic Image Restoration In the Wild
Paper • 2401.13627 • Published • 74