3 papers
cs.CV2026
Diffusing in the Right Space: A Systematic Study of Latent Diffusability
Tianxiong Zhong, Xingye Tian, Xuebo Wang +2
Latent diffusion models leverage visual tokenizers to compress images into latent spaces for efficient generative modeling. However, better reconstruction quality of a tokenizer do…
cs.CV2025
Decoupling Complexity from Scale in Latent Diffusion Model
Tianxiong Zhong, Xingye Tian, Xuebo Wang +3
Existing latent diffusion models typically couple scale with content complexity, using more latent tokens to represent higher-resolution images or higher-frame rate videos. However…
cs.CV2025
Denoising Vision Transformer Autoencoder with Spectral Self-Regularization
Xunzhi Xiang, Xingye Tian, Guiyu Zhang +5
Variational autoencoders (VAEs) typically encode images into a compact latent space, reducing computational cost but introducing an optimization dilemma: a higher-dimensional laten…