3. 计算机视觉

DDPM:Denoising Diffusion Probabilistic Models

DDIM:DENOISING DIFFUSION IMPLICIT MODELS

CDM:Diffusion Models Beat GANs on Image Synthesis

SCORE-BASED GENERATIVE MODELING THROUGH STOCHASTIC DIFFERENTIAL EQUATIONS

CDM:CLASSIFIER-FREE DIFFUSION GUIDANCE

RePaint: Inpainting using Denoising Diffusion Probabilistic Models

Stable Diffusion:High-Resolution Image Synthesis with Latent Diffusion Models

Semi-Parametric Neural Image Synthesis

Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasets

DiT:Scalable Diffusion Models with Transformers

Sora: A Review on Background, Technology, Limitations, and Opportunities of Large Vision Models

Segment Anything

ControlNet:Adding Conditional Control to Text-to-Image Diffusion Models

T2I-Adapter: Learning Adapters to Dig out More Controllable Ability for Text-to-Image Diffusion Models

IP-Adapter: Text Compatible Image Prompt Adapter for Text-to-Image Diffusion Models

Imagen:Photorealistic Text-to-Image Diffusion Models with Deep Language Understanding

DALL·E:Zero-Shot Text-to-Image Generation

DALL·E2:unCLIP:Hierarchical Text-Conditional Image Generation with CLIP Latents

DALL·E3:Improving Image Captioning with Better Use of Captions

VQ-GAN:Taming Transformers for High-Resolution Image Synthesis