8 papers
QuadVerse: An Integrated Framework Aligning Visual-Physical Reality for Quadruped Simulation
Yuxiang Chen, Yuanhao Wang, Ziheng Zhang +6
Simulation is central to robot learning, yet the sim-to-real gap remains a major bottleneck. Existing approaches often tackle visual or dynamic gaps separately, overlooking how the…
FIT: A Large-Scale Dataset for Fit-Aware Virtual Try-On
Johanna Karras, Yuanhao Wang, Yingwei Li +1
Given a person and a garment image, virtual try-on (VTO) aims to synthesize a realistic image of the person wearing the garment, while preserving their original pose and identity.…
From Blurry to Believable: Enhancing Low-quality Talking Heads with 3D Generative Priors
Ding-Jiun Huang, Yuanhao Wang, Shao-Ji Yuan +4
Creating high-fidelity, animatable 3D talking heads is crucial for immersive applications, yet often hindered by the prevalence of low-quality image or video sources, which yield p…
TokBench: Evaluating Your Visual Tokenizer before Visual Generation
Junfeng Wu, Dongliang Luo, Weizhi Zhao +6
In this work, we reveal the limitations of visual tokenizers and VAEs in preserving fine-grained features, and propose a benchmark to evaluate reconstruction performance for two ch…
Unsupervised Detection of Distribution Shift in Inverse Problems using Diffusion Models
Shirin Shoushtari, Edward P. Chandler, Yuanhao Wang +2
Diffusion models are widely used as priors in imaging inverse problems. However, their performance often degrades under distribution shifts between the training and test-time image…
Diff-Unfolding: A Model-Based Score Learning Framework for Inverse Problems
Yuanhao Wang, Shirin Shoushtari, Ulugbek S. Kamilov
Diffusion models are extensively used for modeling image priors for inverse problems. We introduce \emph{Diff-Unfolding}, a principled framework for learning posterior score functi…