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Apr 21
Apr 21
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Collections including paper arxiv:2404.01367
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Jul 3
Jul 3
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Visual Autoregressive Modeling: Scalable Image Generation via Next-Scale Prediction
Paper • 2404.02905 • Published • 64 -
InstantStyle: Free Lunch towards Style-Preserving in Text-to-Image Generation
Paper • 2404.02733 • Published • 20 -
Cross-Attention Makes Inference Cumbersome in Text-to-Image Diffusion Models
Paper • 2404.02747 • Published • 11 -
Bigger is not Always Better: Scaling Properties of Latent Diffusion Models
Paper • 2404.01367 • Published • 20
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Apr 5
Apr 5
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Bigger is not Always Better: Scaling Properties of Latent Diffusion Models
Paper • 2404.01367 • Published • 20 -
On the Scalability of Diffusion-based Text-to-Image Generation
Paper • 2404.02883 • Published • 17 -
Scaling Rectified Flow Transformers for High-Resolution Image Synthesis
Paper • 2403.03206 • Published • 59 -
Improved Denoising Diffusion Probabilistic Models
Paper • 2102.09672 • Published • 2
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Apr 3
Apr 3
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17 days ago
17 days ago
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Lumiere: A Space-Time Diffusion Model for Video Generation
Paper • 2401.12945 • Published • 86 -
Long-form factuality in large language models
Paper • 2403.18802 • Published • 24 -
ObjectDrop: Bootstrapping Counterfactuals for Photorealistic Object Removal and Insertion
Paper • 2403.18818 • Published • 25 -
TC4D: Trajectory-Conditioned Text-to-4D Generation
Paper • 2403.17920 • Published • 16
Collection by
5 days ago
5 days ago
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Demystifying CLIP Data
Paper • 2309.16671 • Published • 20 -
Model Stock: All we need is just a few fine-tuned models
Paper • 2403.19522 • Published • 10 -
Bigger is not Always Better: Scaling Properties of Latent Diffusion Models
Paper • 2404.01367 • Published • 20 -
On the Scalability of Diffusion-based Text-to-Image Generation
Paper • 2404.02883 • Published • 17
Collection by
5 days ago
5 days ago
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U-Net: Convolutional Networks for Biomedical Image Segmentation
Paper • 1505.04597 • Published • 8 -
Image Segmentation using U-Net Architecture for Powder X-ray Diffraction Images
Paper • 2310.16186 • Published • 2 -
H-DenseUNet: Hybrid Densely Connected UNet for Liver and Tumor Segmentation from CT Volumes
Paper • 1709.07330 • Published • 2 -
Deep LOGISMOS: Deep Learning Graph-based 3D Segmentation of Pancreatic Tumors on CT scans
Paper • 1801.08599 • Published • 2