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Ling Pei

18 papers hereh-index 7148 citations24 works total

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

author position
  • middle author1
  • last author16

Across the 17 of 18 papers where every author was matched, so the position is known.

fields
  • cs.CV15
  • cs.LG2
  • cs.RO1
same name
  • Ling Pei — 9 papers, h 4
  • Ling Pei — 4 papers, h 14
  • Ling Pei — 2 papers
  • Ling Pei — 1 paper, h 15
  • Ling Pei — 1 paper, h 2

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

activity
20232026
collaborators
Showing 2026Show all

4 papers · 1 filter

cs.CV2026

IMU-HOI: A Symbiotic Framework for Coherent Human-Object Interaction and Motion Capture via Contact-Conscious Inertial Fusion

Lizhou Lin, Songpengcheng Xia, Zengyuan Lai +3

Capturing full-body human motion with object interactions is crucial for AR/VR and robotics applications, yet it remains challenging for conventional vision-based methods due to oc…

cs.CV2026

G2IA: Geometry-Guided Instance-Aware Retrieval and Refinement for Cross-Modal Place Recognition

Xianyun Jiao, Jingyi Xu, Zhongmiao Yan +2

Cross-modal place recognition (CMPR) enables camera-only robots to localize against pre-built LiDAR maps in autonomous navigation scenarios. This image-to-point-cloud setting is ch…

cs.CV2026

VGGT-MPR: VGGT-Enhanced Multimodal Place Recognition in Autonomous Driving Environments

Jingyi Xu, Zhangshuo Qi, Zhongmiao Yan +5

In autonomous driving, robust place recognition is critical for global localization and loop closure detection. While inter-modality fusion of camera and LiDAR data in multimodal p…

cs.CV2026

360-GeoGS: Geometrically Consistent Feed-Forward 3D Gaussian Splatting Reconstruction for 360 Images

Jiaqi Yao, Zhongmiao Yan, Jingyi Xu +3

3D scene reconstruction is fundamental for spatial intelligence applications such as AR, robotics, and digital twins. Traditional multi-view stereo struggles with sparse viewpoints…

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