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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 • 39 -
EfficientViT-SAM: Accelerated Segment Anything Model Without Performance Loss
Paper • 2402.05008 • Published • 20
Collections
Discover the best community collections!
Collections including paper arxiv:2411.17949
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LinFusion: 1 GPU, 1 Minute, 16K Image
Paper • 2409.02097 • Published • 32 -
Phidias: A Generative Model for Creating 3D Content from Text, Image, and 3D Conditions with Reference-Augmented Diffusion
Paper • 2409.11406 • Published • 25 -
Diffusion Models Are Real-Time Game Engines
Paper • 2408.14837 • Published • 121 -
Segment Anything with Multiple Modalities
Paper • 2408.09085 • Published • 21
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OpenCoder: The Open Cookbook for Top-Tier Code Large Language Models
Paper • 2411.04905 • Published • 111 -
LLaVA-o1: Let Vision Language Models Reason Step-by-Step
Paper • 2411.10440 • Published • 111 -
Marco-o1: Towards Open Reasoning Models for Open-Ended Solutions
Paper • 2411.14405 • Published • 58 -
ROICtrl: Boosting Instance Control for Visual Generation
Paper • 2411.17949 • Published • 82
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Generating Compositional Scenes via Text-to-image RGBA Instance Generation
Paper • 2411.10913 • Published • 3 -
ROICtrl: Boosting Instance Control for Visual Generation
Paper • 2411.17949 • Published • 82 -
Pathways on the Image Manifold: Image Editing via Video Generation
Paper • 2411.16819 • Published • 30
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MobileCLIP: Fast Image-Text Models through Multi-Modal Reinforced Training
Paper • 2311.17049 • Published • 1 -
DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model
Paper • 2405.04434 • Published • 14 -
A Study of Autoregressive Decoders for Multi-Tasking in Computer Vision
Paper • 2303.17376 • Published -
Sigmoid Loss for Language Image Pre-Training
Paper • 2303.15343 • Published • 5
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Compose and Conquer: Diffusion-Based 3D Depth Aware Composable Image Synthesis
Paper • 2401.09048 • Published • 9 -
Improving fine-grained understanding in image-text pre-training
Paper • 2401.09865 • Published • 16 -
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 • 73