4 papers
Understand Before You Generate: Self-Guided Training for Autoregressive Image Generation
Xiaoyu Yue, Zidong Wang, Yuqing Wang +5
Recent studies have demonstrated the importance of high-quality visual representations in image generation and have highlighted the limitations of generative models in image unders…
Transition Models: Rethinking the Generative Learning Objective
Zidong Wang, Yiyuan Zhang, Xiaoyu Yue +4
A fundamental dilemma in generative modeling persists: iterative diffusion models achieve outstanding fidelity, but at a significant computational cost, while efficient few-step al…
Native-Resolution Image Synthesis
Zidong Wang, Lei Bai, Xiangyu Yue +2
We introduce native-resolution image synthesis, a novel generative modeling paradigm that enables the synthesis of images at arbitrary resolutions and aspect ratios. This approach…
Exploring Representation-Aligned Latent Space for Better Generation
Wanghan Xu, Xiaoyu Yue, Zidong Wang +6
Generative models serve as powerful tools for modeling the real world, with mainstream diffusion models, particularly those based on the latent diffusion model paradigm, achieving…