6 papers
Flowing Backwards: Improving Normalizing Flows via Reverse Representation Alignment
Yang Chen, Xiaowei Xu, Shuai Wang +5
Normalizing Flows (NFs) are a class of generative models distinguished by a mathematically invertible architecture, where the forward pass transforms data into a latent space for d…
MotionRAG: Motion Retrieval-Augmented Image-to-Video Generation
Chenhui Zhu, Yilu Wu, Shuai Wang +2
Image-to-video generation has made remarkable progress with the advancements in diffusion models, yet generating videos with realistic motion remains highly challenging. This diffi…
PixNerd: Pixel Neural Field Diffusion
Shuai Wang, Ziteng Gao, Chenhui Zhu +2
The current success of diffusion transformers heavily depends on the compressed latent space shaped by the pre-trained variational autoencoder(VAE). However, this two-stage trainin…
Differentiable Solver Search for Fast Diffusion Sampling
Shuai Wang, Zexian Li, Qipeng zhang +5
Diffusion models have demonstrated remarkable generation quality but at the cost of numerous function evaluations. Recently, advanced ODE-based solvers have been developed to mitig…
DMM: Building a Versatile Image Generation Model via Distillation-Based Model Merging
Tianhui Song, Weixin Feng, Shuai Wang +4
The success of text-to-image (T2I) generation models has spurred a proliferation of numerous model checkpoints fine-tuned from the same base model on various specialized datasets.…
Learning Human Skill Generators at Key-Step Levels
Yilu Wu, Chenhui Zhu, Shuai Wang +4
We are committed to learning human skill generators at key-step levels. The generation of skills is a challenging endeavor, but its successful implementation could greatly facilita…