9 papers
MIMFlow: Integrating Masked Image Modeling with Normalizing Flows for End-to-End Image Generation
Yang Chen, Xiaowei Xu, Shuai Wang +4
Normalizing Flows (NFs) are powerful generative models capable of exact density estimation and sampling. However, their strict invertibility often forces the model to exhaust its c…
UniDDT: Unifying Multimodal Understanding and Generation with Decoupled Diffusion Transformer
Shuai Wang, Liang Li, Yang Chen +3
Unified Multimodal Models (UMMs) have emerged as a critical direction for general-purpose multimodal intelligence, integrating understanding and generation into a single framework.…
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…