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Peng Li

10 papers hereh-index 6180 citations11 works total

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

author position
  • first author2
  • middle author2
  • last author3

Across the 7 of 10 papers where every author was matched, so the position is known.

fields
  • cs.CV6
  • cs.LG3
  • cs.NE1
same name
  • Peng Li — 59 papers, h 37
  • Peng Li — 46 papers, h 65
  • Peng Li — 16 papers, h 13
  • Peng Li — 15 papers, h 5
  • Peng Li — 14 papers, h 12
  • Peng Li — 14 papers, h 3

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
20182022
most citedExploiting Offset-guided Network for Pose Estimation and Tracking

14 citations · 23 across the 5 of their papers we have counts for

collaborators
Showing 2019Show all

4 papers · 1 filter

cs.CV2019

FastPose: Towards Real-time Pose Estimation and Tracking via Scale-normalized Multi-task Networks

Jiabin Zhang, Zheng Zhu, Wei Zou +4

Both accuracy and efficiency are significant for pose estimation and tracking in videos. State-of-the-art performance is dominated by two-stages top-down methods. Despite the leadi…

cs.CV2019★ 4 cited

State-aware Re-identification Feature for Multi-target Multi-camera Tracking

Peng Li, Jiabin Zhang, Zheng Zhu +3

Multi-target Multi-camera Tracking (MTMCT) aims to extract the trajectories from videos captured by a set of cameras. Recently, the tracking performance of MTMCT is significantly e…

cs.CV2019★ 14 cited

Exploiting Offset-guided Network for Pose Estimation and Tracking

Rui Zhang, Zheng Zhu, Peng Li +4

Human pose estimation has witnessed a significant advance thanks to the development of deep learning. Recent human pose estimation approaches tend to directly predict the location…

cs.LG2019

Robust Deep Multi-Modal Sensor Fusion using Fusion Weight Regularization and Target Learning

Myung Seok Shim, Chenye Zhao, Yang Li +3

Sensor fusion has wide applications in many domains including health care and autonomous systems. While the advent of deep learning has enabled promising multi-modal fusion of high…

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