52 citations · 112 across the 10 of their papers we have counts for
11 papers
Efficient-VQGAN: Towards High-Resolution Image Generation with Efficient Vision Transformers
Shiyue Cao, Yueqin Yin, Lianghua Huang +4
Vector-quantized image modeling has shown great potential in synthesizing high-quality images. However, generating high-resolution images remains a challenging task due to the quad…
AnyDoor: Zero-shot Object-level Image Customization
Xi Chen, Lianghua Huang, Yu Liu +3
This work presents AnyDoor, a diffusion-based image generator with the power to teleport target objects to new scenes at user-specified locations in a harmonious way. Instead of tu…
Lipschitz Singularities in Diffusion Models
Zhantao Yang, Ruili Feng, Han Zhang +8
Diffusion models, which employ stochastic differential equations to sample images through integrals, have emerged as a dominant class of generative models. However, the rationality…
Composer: Creative and Controllable Image Synthesis with Composable Conditions
Lianghua Huang, Di Chen, Yu Liu +3
Recent large-scale generative models learned on big data are capable of synthesizing incredible images yet suffer from limited controllability. This work offers a new generation pa…
Dimensionality-Varying Diffusion Process
Han Zhang, Ruili Feng, Zhantao Yang +7
Diffusion models, which learn to reverse a signal destruction process to generate new data, typically require the signal at each step to have the same dimension. We argue that, con…
DiffGAR: Model-Agnostic Restoration from Generative Artifacts Using Image-to-Image Diffusion Models
Yueqin Yin, Lianghua Huang, Yu Liu +1
Recent generative models show impressive results in photo-realistic image generation. However, artifacts often inevitably appear in the generated results, leading to downgraded use…