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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 • 19 -
Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data
Paper • 2401.10891 • Published • 64 -
Scaling Up to Excellence: Practicing Model Scaling for Photo-Realistic Image Restoration In the Wild
Paper • 2401.13627 • Published • 78
Collections
Discover the best community collections!
Collections including paper arxiv:2502.20126
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MangaNinja: Line Art Colorization with Precise Reference Following
Paper • 2501.08332 • Published • 62 -
Inference-Time Scaling for Diffusion Models beyond Scaling Denoising Steps
Paper • 2501.09732 • Published • 72 -
FlexiDiT: Your Diffusion Transformer Can Easily Generate High-Quality Samples with Less Compute
Paper • 2502.20126 • Published • 19 -
Lean and Mean: Decoupled Value Policy Optimization with Global Value Guidance
Paper • 2502.16944 • Published • 10
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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 • 19 -
Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data
Paper • 2401.10891 • Published • 64 -
Scaling Up to Excellence: Practicing Model Scaling for Photo-Realistic Image Restoration In the Wild
Paper • 2401.13627 • Published • 78
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FlashAttention: Fast and Memory-Efficient Exact Attention with IO-Awareness
Paper • 2205.14135 • Published • 16 -
FlashAttention-2: Faster Attention with Better Parallelism and Work Partitioning
Paper • 2307.08691 • Published • 10 -
FlashAttention-3: Fast and Accurate Attention with Asynchrony and Low-precision
Paper • 2407.08608 • Published • 2 -
1.58-bit FLUX
Paper • 2412.18653 • Published • 87
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1.58-bit FLUX
Paper • 2412.18653 • Published • 87 -
Region-Adaptive Sampling for Diffusion Transformers
Paper • 2502.10389 • Published • 53 -
One-step Diffusion Models with f-Divergence Distribution Matching
Paper • 2502.15681 • Published • 8 -
FlexiDiT: Your Diffusion Transformer Can Easily Generate High-Quality Samples with Less Compute
Paper • 2502.20126 • Published • 19
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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 • 19 -
Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data
Paper • 2401.10891 • Published • 64 -
Scaling Up to Excellence: Practicing Model Scaling for Photo-Realistic Image Restoration In the Wild
Paper • 2401.13627 • Published • 78
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FlashAttention: Fast and Memory-Efficient Exact Attention with IO-Awareness
Paper • 2205.14135 • Published • 16 -
FlashAttention-2: Faster Attention with Better Parallelism and Work Partitioning
Paper • 2307.08691 • Published • 10 -
FlashAttention-3: Fast and Accurate Attention with Asynchrony and Low-precision
Paper • 2407.08608 • Published • 2 -
1.58-bit FLUX
Paper • 2412.18653 • Published • 87
-
MangaNinja: Line Art Colorization with Precise Reference Following
Paper • 2501.08332 • Published • 62 -
Inference-Time Scaling for Diffusion Models beyond Scaling Denoising Steps
Paper • 2501.09732 • Published • 72 -
FlexiDiT: Your Diffusion Transformer Can Easily Generate High-Quality Samples with Less Compute
Paper • 2502.20126 • Published • 19 -
Lean and Mean: Decoupled Value Policy Optimization with Global Value Guidance
Paper • 2502.16944 • Published • 10
-
1.58-bit FLUX
Paper • 2412.18653 • Published • 87 -
Region-Adaptive Sampling for Diffusion Transformers
Paper • 2502.10389 • Published • 53 -
One-step Diffusion Models with f-Divergence Distribution Matching
Paper • 2502.15681 • Published • 8 -
FlexiDiT: Your Diffusion Transformer Can Easily Generate High-Quality Samples with Less Compute
Paper • 2502.20126 • Published • 19
-
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 • 19 -
Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data
Paper • 2401.10891 • Published • 64 -
Scaling Up to Excellence: Practicing Model Scaling for Photo-Realistic Image Restoration In the Wild
Paper • 2401.13627 • Published • 78