12 papers
Muddit: Liberating Generation Beyond Text-to-Image with a Unified Discrete Diffusion Model
Qingyu Shi, Jinbin Bai, Zhuoran Zhao +7
Unified generation models aim to handle diverse tasks across modalities -- such as text generation, image generation, and vision-language reasoning -- within a single architecture…
EditMGT: Unleashing Potentials of Masked Generative Transformers in Image Editing
Wei Chow, Linfeng Li, Lingdong Kong +13
Recent advances in diffusion models (DMs) have achieved exceptional visual quality in image editing tasks. However, the global denoising dynamics of DMs inherently conflate local e…
Personalized Safety Alignment for Text-to-Image Diffusion Models
Yu Lei, Jinbin Bai, Qingyu Shi +4
Text-to-image diffusion models have revolutionized visual content generation, yet their deployment is hindered by a fundamental limitation: safety mechanisms enforce rigid, uniform…
RecTok: Reconstruction Distillation along Rectified Flow
Qingyu Shi, Size Wu, Jinbin Bai +5
Visual tokenizers play a crucial role in diffusion models. The dimensionality of latent space governs both reconstruction fidelity and the semantic expressiveness of the latent fea…
Conditional Panoramic Image Generation via Masked Autoregressive Modeling
Chaoyang Wang, Xiangtai Li, Lu Qi +4
Recent progress in panoramic image generation has underscored two critical limitations in existing approaches. First, most methods are built upon diffusion models, which are inhere…
Decouple and Track: Benchmarking and Improving Video Diffusion Transformers for Motion Transfer
Qingyu Shi, Jianzong Wu, Jinbin Bai +4
The motion transfer task aims to transfer motion from a source video to newly generated videos, requiring the model to decouple motion from appearance. Previous diffusion-based met…