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20172022
most citedMovement science needs different pose tracking algorithms

68 citations · 84 across the 8 of their papers we have counts for

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8 papers · 1 filter

cs.CV20221 cited

ARAH: Animatable Volume Rendering of Articulated Human SDFs

Shaofei Wang, Katja Schwarz, Andreas Geiger +1

Combining human body models with differentiable rendering has recently enabled animatable avatars of clothed humans from sparse sets of multi-view RGB videos. While state-of-the-ar…

cs.CV2021

Locally Aware Piecewise Transformation Fields for 3D Human Mesh Registration

Shaofei Wang, Andreas Geiger, Siyu Tang

Registering point clouds of dressed humans to parametric human models is a challenging task in computer vision. Traditional approaches often rely on heavily engineered pipelines th…

cs.CV2019

End-to-end Training of CNN-CRF via Differentiable Dual-Decomposition

Shaofei Wang, Vishnu Lokhande, Maneesh Singh +2

Modern computer vision (CV) is often based on convolutional neural networks (CNNs) that excel at hierarchical feature extraction. The previous generation of CV approaches was often…

cs.CV201968 cited

Movement science needs different pose tracking algorithms

Nidhi Seethapathi, Shaofei Wang, Rachit Saluja +2

Over the last decade, computer science has made progress towards extracting body pose from single camera photographs or videos. This promises to enable movement science to detect d…

cs.CV20171 cited

Efficient Multi-Person Pose Estimation with Provable Guarantees

Shaofei Wang, Konrad Paul Kording, Julian Yarkony

Multi-person pose estimation (MPPE) in natural images is key to the meaningful use of visual data in many fields including movement science, security, and rehabilitation. In this p…

cs.CV20174 cited

Efficient Column Generation for Cell Detection and Segmentation

Chong Zhang, Shaofei Wang, Miguel A. Gonzalez-Ballester +1

We study the problem of instance segmentation in biological images with crowded and compact cells. We formulate this task as an integer program where variables correspond to cells…