Adversarial Diffusion Distillation 论文阅读
Improving Sample Quality of Diffusion Models Using Self-Attention Guidance 论文阅读
yysy，挺有意思
Training-Free Layout Control with Cross-Attention Guidance 论文阅读
(CVPR2022-Oral) Perception Prioritized Training of Diffusion Models
Diffusion Model & AutoEncoder
DM检测论文阅读
Detecting Images Generated by Deep Diffusion Models using their Local Intrinsic Dimensionality
(ACM 2023)Parents and Children: Distinguishing Multimodal DeepFakes from Natural Images 论文阅读
(ICLR 2022)SDEDIT: GUIDED IMAGE SYNTHESIS AND EDITING WITH STOCHASTIC DIFFERE 论文阅读
(CVPR2023)DCFace: Synthetic Face Generation with Dual Condition Diffusion Model 论文阅读
RGBD2: Generative Scene Synthesis via Incremental View Inpainting using RGBD Diffusion Models 论文阅读
Prompt-to-Prompt Image Editing with Cross Attention Control 论文阅读
Magic3D: High-Resolution Text-to-3D Content Creation 论文阅读
(CVPR2023)DiffRF: Rendering-Guided 3D Radiance Field Diffusion 论文阅读
感觉8行
(CVPR2023)Diffusion-SDF: Text-to-Shape via Voxelized Diffusion
(ICLR2023)DIFFUSION PROBABILISTIC FIELDS
(CVPR2023)DiffPose: Toward More Reliable 3D Pose Estimation 论文阅读
1. 扩散过程的最终结果 不是高斯噪声, 而是 Coarse Estimate Distribution. 2. 使用 GMM 重新建模 , 使得扩散的中间结果的分布带有方差信息. @2023.06.03 突然发现这篇文章中CVPR了 质量确实不错
(ICML2023)NerfDiff: Single-image View Synthesis with NeRF-guided Distillation from 3D-aware Diffusion 论文阅读
eq7看不懂了
(CVPR2023)HOLODIFFUSION: Training a 3D Diffusion Model using 2D Images-论文阅读
初看感觉没道理 再看其实挺有道理的 感觉可以直接用到弱监督