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A Comprehensive Survey of Mamba Architectures for Medical Image Analysis: Classification, Segmentation, Restoration and Beyond
Paper • 2410.02362 • Published • 18 -
CheXagent: Towards a Foundation Model for Chest X-Ray Interpretation
Paper • 2401.12208 • Published • 22 -
Reliable Tuberculosis Detection using Chest X-ray with Deep Learning, Segmentation and Visualization
Paper • 2007.14895 • Published • 1 -
Explanatory Instructions: Towards Unified Vision Tasks Understanding and Zero-shot Generalization
Paper • 2412.18525 • Published • 75
Collections
Discover the best community collections!
Collections including paper arxiv:2501.05441
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EVA-CLIP-18B: Scaling CLIP to 18 Billion Parameters
Paper • 2402.04252 • Published • 29 -
Vision Superalignment: Weak-to-Strong Generalization for Vision Foundation Models
Paper • 2402.03749 • Published • 14 -
ScreenAI: A Vision-Language Model for UI and Infographics Understanding
Paper • 2402.04615 • Published • 44 -
EfficientViT-SAM: Accelerated Segment Anything Model Without Performance Loss
Paper • 2402.05008 • Published • 23
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Depth Anything V2
Paper • 2406.09414 • Published • 103 -
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 • 39 -
SAM 2: Segment Anything in Images and Videos
Paper • 2408.00714 • Published • 119
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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 • 18 -
Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data
Paper • 2401.10891 • Published • 62 -
Scaling Up to Excellence: Practicing Model Scaling for Photo-Realistic Image Restoration In the Wild
Paper • 2401.13627 • Published • 77
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A Comprehensive Survey of Mamba Architectures for Medical Image Analysis: Classification, Segmentation, Restoration and Beyond
Paper • 2410.02362 • Published • 18 -
CheXagent: Towards a Foundation Model for Chest X-Ray Interpretation
Paper • 2401.12208 • Published • 22 -
Reliable Tuberculosis Detection using Chest X-ray with Deep Learning, Segmentation and Visualization
Paper • 2007.14895 • Published • 1 -
Explanatory Instructions: Towards Unified Vision Tasks Understanding and Zero-shot Generalization
Paper • 2412.18525 • Published • 75
-
Depth Anything V2
Paper • 2406.09414 • Published • 103 -
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 • 39 -
SAM 2: Segment Anything in Images and Videos
Paper • 2408.00714 • Published • 119
-
EVA-CLIP-18B: Scaling CLIP to 18 Billion Parameters
Paper • 2402.04252 • Published • 29 -
Vision Superalignment: Weak-to-Strong Generalization for Vision Foundation Models
Paper • 2402.03749 • Published • 14 -
ScreenAI: A Vision-Language Model for UI and Infographics Understanding
Paper • 2402.04615 • Published • 44 -
EfficientViT-SAM: Accelerated Segment Anything Model Without Performance Loss
Paper • 2402.05008 • Published • 23
-
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 • 18 -
Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data
Paper • 2401.10891 • Published • 62 -
Scaling Up to Excellence: Practicing Model Scaling for Photo-Realistic Image Restoration In the Wild
Paper • 2401.13627 • Published • 77