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Feng Xu

5 papers here

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author1
  • last author4

Across the 5 of 5 papers where every author was matched, so the position is known.

fields
  • cs.CV4
  • cs.LG1
ORCID 0000-0002-0953-1057
same name
  • Feng Xu — 10 papers, h 27
  • Feng Xu — 7 papers, h 33
  • Feng Xu — 7 papers, h 22
  • Feng Xu — 4 papers
  • Feng Xu — 4 papers, h 3
  • Feng Xu — 3 papers

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

most citedHow To Guide Your Learner: Imitation Learning with Active Adaptive Expert Involvement

3 citations · 5 across the 5 of their papers we have counts for

collaborators

4 papers

cs.CV2023★ 2 cited

EgoLocate: Real-time Motion Capture, Localization, and Mapping with Sparse Body-mounted Sensors

Xinyu Yi, Yuxiao Zhou, Marc Habermann +4

Human and environment sensing are two important topics in Computer Vision and Graphics. Human motion is often captured by inertial sensors, while the environment is mostly reconstr…

cs.CV2023

Learning a 3D Morphable Face Reflectance Model from Low-cost Data

Yuxuan Han, Zhibo Wang, Feng Xu

Modeling non-Lambertian effects such as facial specularity leads to a more realistic 3D Morphable Face Model. Existing works build parametric models for diffuse and specular albedo…

cs.LG2023★ 3 cited

How To Guide Your Learner: Imitation Learning with Active Adaptive Expert Involvement

Xu-Hui Liu, Feng Xu, Xinyu Zhang +5

Imitation learning aims to mimic the behavior of experts without explicit reward signals. Passive imitation learning methods which use static expert datasets typically suffer from…

cs.CV2022

Structure-aware Editable Morphable Model for 3D Facial Detail Animation and Manipulation

Jingwang Ling, Zhibo Wang, Ming Lu +3

Morphable models are essential for the statistical modeling of 3D faces. Previous works on morphable models mostly focus on large-scale facial geometry but ignore facial details. T…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.