Latent Diffusion and State-of-the-Art Models

Slides
Video Lecture

References

  1. High-Resolution Image Synthesis with Latent Diffusion ModelsRobin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, Björn Ommer2021
  2. Zero-Shot Text-to-Image GenerationAditya Ramesh, Mikhail Pavlov, Gabriel Goh, Scott Gray, Chelsea Voss, Alec Radford, Mark Chen, etal.2021
  3. Photorealistic Text-to-Image Diffusion Models with Deep Language UnderstandingChitwan Saharia, William Chan, Saurabh Saxena, Lala Li, Jay Whang, Emily Denton, etal.2022
  4. Hierarchical Text-Conditional Image Generation with CLIP LatentsAditya Ramesh, Prafulla Dhariwal, Alex Nichol, Casey Chu, Mark Chen2022
  5. CCM: Adding Conditional Controls to Text-to-Image Consistency ModelsJie Xiao, Kai Zhu, Han Zhang, Zhiheng Liu, Yujun Shen, Yu Liu, Xueyang Fu, Zheng-Jun Zha2023
  6. Adding Conditional Control to Text-to-Image Diffusion ModelsLvmin Zhang, Anyi Rao, Maneesh Agrawala2023
  7. One-step Diffusion with Distribution Matching DistillationTianwei Yin, Michaël Gharbi, Richard Zhang, Eli Shechtman, Fredo Durand, William T. Freeman, etal.2023
  8. Diffusion Models: A Comprehensive Survey of Methods and ApplicationsLing Yang, Zhilong Zhang, Yang Song, Shenda Hong, Runsheng Xu, Yue Zhao, Wentao Zhang, Bin Cui, etal.2022