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Yufu Wang

8 accepted papers

2026

DuoMo: Dual Motion Diffusion for World-Space Human Reconstruction

CVPR 2026

We present DuoMo, a generative method that recovers human motion in world-space coordinates from unconstrained videos with noisy or incomplete observations. Reconstructing such motion requires solving a fundamental trade-off: generalizing from diverse and noisy video inputs while maintaining global

Cited by 0SourcecodeScholar
2026

OnlineHMR: Video-based Online World-Grounded Human Mesh Recovery

CVPR 2026

Human mesh recovery (HMR) models 3D human body from monocular videos, with recent works extending it to world-coordinate human trajectory and motion reconstruction. However, most existing methods remain offline, relying on future frames or global optimization, which limits their applicability in int

Cited by 0SourcecodeScholar
2025

Continuous-Time Human Motion Field from Event Cameras

ICCV 2025poster

This paper addresses the challenges of estimating a continuous-time field from a stream of events. Existing Human Mesh Recovery (HMR) methods rely predominantly on frame-based approaches, which are prone to aliasing and inaccuracies due to limited temporal resolution and motion blur. In this work, w…

Cited by 0SourcePDFScholar
2025

PromptHMR: Promptable Human Mesh Recovery

CVPR 2025poster

Human pose and shape (HPS) estimation presents challenges in diverse scenarios such as crowded scenes, person-person interactions, and single-view reconstruction. Existing approaches lack mechanisms to incorporate auxiliary "side information" that could enhance reconstruction accuracy in such challe…

Cited by 0SourcePDFScholar
2024

GART: Gaussian Articulated Template Models

CVPR 2024highlight

We introduce Gaussian Articulated Template Model (GART) an explicit efficient and expressive representation for non-rigid articulated subject capturing and rendering from monocular videos. GART utilizes a mixture of moving 3D Gaussians to explicitly approximate a deformable subject's geometry and ap…

Cited by 94SourcePDFScholar
2021

Birds of a Feather: Capturing Avian Shape Models From Images

CVPR 2021poster

Animals are diverse in shape, but building a deformable shape model for a new species is not always possible due to the lack of 3D data. We present a method to capture new species using an articulated template and images of that species. In this work, we focus mainly on birds. Although birds represe…

Cited by 32PDFcodeScholar
2020

3D Bird Reconstruction: a Dataset, Model, and Shape Recovery from a Single View

ECCV 2020poster

Model, and Shape Recovery from a Single View","Automated capture of animal pose is transforming how we study neuroscience and social behavior. Movements carry important social cues, but current methods are not able to robustly estimate pose and shape of animals, particularly for social animals such…