activity
20222026
most citedNeAT: Neural Adaptive Tomography

8 citations · 9 across the 9 of their papers we have counts for

collaborators

10 papers

q-bio.BM2026

Reconstruction-Aware Cryo-EM Particle Picking

Riku Itsuji, Yuanhao Wang, Xingjian Li +3

Cryo-electron microscopy (cryo-EM) determines the structures of proteins and macromolecular assemblies at near-atomic resolution, and the final 3D reconstruction depends on extract…

cs.RO2026

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…

cs.CV2026

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.…

cs.CV2026

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…

cs.CV2025

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…

cs.CV2025

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…

eess.IV2025

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…

cs.GR2025

GarmentCrafter: Progressive Novel View Synthesis for Single-View 3D Garment Reconstruction and Editing

Yuanhao Wang, Cheng Zhang, Gonçalo Frazão +4

We introduce GarmentCrafter, a new approach that enables non-professional users to create and modify 3D garments from a single-view image. While recent advances in image generation…

cs.CV2024★ 1 cited

FabricDiffusion: High-Fidelity Texture Transfer for 3D Garments Generation from In-The-Wild Clothing Images

Cheng Zhang, Yuanhao Wang, Francisco Vicente Carrasco +4

We introduce FabricDiffusion, a method for transferring fabric textures from a single clothing image to 3D garments of arbitrary shapes. Existing approaches typically synthesize te…

cs.CV2022★ 8 cited

NeAT: Neural Adaptive Tomography

Darius Rückert, Yuanhao Wang, Rui Li +2

In this paper, we present Neural Adaptive Tomography (NeAT), the first adaptive, hierarchical neural rendering pipeline for multi-view inverse rendering. Through a combination of n…