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LinFusion: 1 GPU, 1 Minute, 16K Image
Paper • 2409.02097 • Published • 33 -
Phidias: A Generative Model for Creating 3D Content from Text, Image, and 3D Conditions with Reference-Augmented Diffusion
Paper • 2409.11406 • Published • 26 -
Diffusion Models Are Real-Time Game Engines
Paper • 2408.14837 • Published • 123 -
Segment Anything with Multiple Modalities
Paper • 2408.09085 • Published • 22
Collections
Discover the best community collections!
Collections including paper arxiv:2501.09756
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Can Large Language Models Understand Context?
Paper • 2402.00858 • Published • 23 -
OLMo: Accelerating the Science of Language Models
Paper • 2402.00838 • Published • 83 -
Self-Rewarding Language Models
Paper • 2401.10020 • Published • 146 -
SemScore: Automated Evaluation of Instruction-Tuned LLMs based on Semantic Textual Similarity
Paper • 2401.17072 • Published • 25
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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
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Colorful Diffuse Intrinsic Image Decomposition in the Wild
Paper • 2409.13690 • Published • 13 -
Latent Intrinsics Emerge from Training to Relight
Paper • 2405.21074 • Published • 1 -
Reflecting Reality: Enabling Diffusion Models to Produce Faithful Mirror Reflections
Paper • 2409.14677 • Published • 15 -
SynthLight: Portrait Relighting with Diffusion Model by Learning to Re-render Synthetic Faces
Paper • 2501.09756 • Published • 19
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Boundary Attention: Learning to Find Faint Boundaries at Any Resolution
Paper • 2401.00935 • Published • 18 -
Derendering/InkSight-Small-p
Updated • 36 • 28 -
E^{2}GAN: Efficient Training of Efficient GANs for Image-to-Image Translation
Paper • 2401.06127 • Published -
Acoustic Volume Rendering for Neural Impulse Response Fields
Paper • 2411.06307 • Published • 5