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Samba: Semantic Segmentation of Remotely Sensed Images with State Space Model
Paper • 2404.01705 • Published -
SemPLeS: Semantic Prompt Learning for Weakly-Supervised Semantic Segmentation
Paper • 2401.11791 • Published • 1 -
ITACLIP: Boosting Training-Free Semantic Segmentation with Image, Text, and Architectural Enhancements
Paper • 2411.12044 • Published • 14 -
Semi-Supervised Semantic Segmentation using Redesigned Self-Training for White Blood Cells
Paper • 2401.07278 • Published • 2
Collections
Discover the best community collections!
Collections including paper arxiv:2411.12044
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LinFusion: 1 GPU, 1 Minute, 16K Image
Paper • 2409.02097 • Published • 34 -
Phidias: A Generative Model for Creating 3D Content from Text, Image, and 3D Conditions with Reference-Augmented Diffusion
Paper • 2409.11406 • Published • 27 -
Diffusion Models Are Real-Time Game Engines
Paper • 2408.14837 • Published • 126 -
Segment Anything with Multiple Modalities
Paper • 2408.09085 • Published • 22
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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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LocalMamba: Visual State Space Model with Windowed Selective Scan
Paper • 2403.09338 • Published • 9 -
GiT: Towards Generalist Vision Transformer through Universal Language Interface
Paper • 2403.09394 • Published • 27 -
Panda-70M: Captioning 70M Videos with Multiple Cross-Modality Teachers
Paper • 2402.19479 • Published • 35 -
Grounding DINO 1.5: Advance the "Edge" of Open-Set Object Detection
Paper • 2405.10300 • Published • 30
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Samba: Semantic Segmentation of Remotely Sensed Images with State Space Model
Paper • 2404.01705 • Published -
SemPLeS: Semantic Prompt Learning for Weakly-Supervised Semantic Segmentation
Paper • 2401.11791 • Published • 1 -
ITACLIP: Boosting Training-Free Semantic Segmentation with Image, Text, and Architectural Enhancements
Paper • 2411.12044 • Published • 14 -
Semi-Supervised Semantic Segmentation using Redesigned Self-Training for White Blood Cells
Paper • 2401.07278 • Published • 2
-
LinFusion: 1 GPU, 1 Minute, 16K Image
Paper • 2409.02097 • Published • 34 -
Phidias: A Generative Model for Creating 3D Content from Text, Image, and 3D Conditions with Reference-Augmented Diffusion
Paper • 2409.11406 • Published • 27 -
Diffusion Models Are Real-Time Game Engines
Paper • 2408.14837 • Published • 126 -
Segment Anything with Multiple Modalities
Paper • 2408.09085 • Published • 22
-
LocalMamba: Visual State Space Model with Windowed Selective Scan
Paper • 2403.09338 • Published • 9 -
GiT: Towards Generalist Vision Transformer through Universal Language Interface
Paper • 2403.09394 • Published • 27 -
Panda-70M: Captioning 70M Videos with Multiple Cross-Modality Teachers
Paper • 2402.19479 • Published • 35 -
Grounding DINO 1.5: Advance the "Edge" of Open-Set Object Detection
Paper • 2405.10300 • Published • 30
-
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