Yuliang Xiu

Yuliang Xiu
Max Planck Institute for Intelligent Systems | IS · Perceiving Systems Department

Doctor of Engineering
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About

12
Publications
3,350
Reads
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375
Citations
Citations since 2017
12 Research Items
375 Citations
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2017201820192020202120222023020406080100120140
2017201820192020202120222023020406080100120140
Introduction
My research lies in the intersection of vision and graphics, especially in 3D Human Digitization.
Education
November 2020 - November 2023
Max Planck Institute for Intelligent Systems
Field of study
  • Computer Science and Engineering
August 2019 - October 2020
University of Southern California
Field of study
  • Computer Science and Engineering
September 2016 - March 2019
Shanghai Jiao Tong University
Field of study
  • Computer Science and Engineering

Publications

Publications (12)
Conference Paper
Full-text available
Multi-person articulated pose tracking in complex unconstrained videos is an important and challenging problem. In this paper, going along the road of top-down approaches, we propose a decent and efficient pose tracker based on pose flows. First, we design an online optimization framework to build association of cross-frame poses and form pose flow...
Chapter
Full-text available
We present the first approach to volumetric performance capture and novel-view rendering at real-time speed from monocular video, eliminating the need for expensive multi-view systems or cumbersome pre-acquisition of a personalized template model. Our system reconstructs a fully textured 3D human from each frame by leveraging Pixel-Aligned Implicit...
Preprint
Full-text available
Current methods for learning realistic and animatable 3D clothed avatars need either posed 3D scans or 2D images with carefully controlled user poses. In contrast, our goal is to learn the avatar from only 2D images of people in unconstrained poses. Given a set of images, our method estimates a detailed 3D surface from each image and then combines...
Preprint
Full-text available
The combination of artist-curated scans, and deep implicit functions (IF), is enabling the creation of detailed, clothed, 3D humans from images. However, existing methods are far from perfect. IF-based methods recover free-form geometry but produce disembodied limbs or degenerate shapes for unseen poses or clothes. To increase robustness for these...
Article
Full-text available
Accurate whole-body multi-person pose estimation and tracking is an important yet challenging topic in computer vision. To capture the subtle actions of humans for complex behavior analysis, whole-body pose estimation including the face, body, hand and foot is essential over conventional body-only pose estimation. In this paper, we present AlphaPos...
Preprint
Full-text available
Accurate whole-body multi-person pose estimation and tracking is an important yet challenging topic in computer vision. To capture the subtle actions of humans for complex behavior analysis, whole-body pose estimation including the face, body, hand and foot is essential over conventional body-only pose estimation. In this paper, we present AlphaPos...
Preprint
Full-text available
Hand, the bearer of human productivity and intelligence, is receiving much attention due to the recent fever of digital twins. Among different hand morphable models, MANO has been widely used in vision and graphics community. However, MANO disregards textures and accessories, which largely limits its power to synthesize photorealistic hand data. In...
Preprint
Full-text available
We present the first approach to volumetric performance capture and novel-view rendering at real-time speed from monocular video, eliminating the need for expensive multi-view systems or cumbersome pre-acquisition of a personalized template model. Our system reconstructs a fully textured 3D human from each frame by leveraging Pixel-Aligned Implicit...
Article
Full-text available
As most recently proposed methods for human detection have achieved a sufficiently high recall rate within a reasonable number of proposals, in this paper, we mainly focus on how to improve the precision rate of human detectors. In order to address the two main challenges in precision improvement, i.e., i) hard background instances and ii) redundan...

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