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Pu Li

4 papers here

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

author position
  • first author1
  • middle author1
  • last author2

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.CV4
ORCID 0009-0007-1410-4096
same name
  • Pu Li — 7 papers, h 16
  • Pu Li — 4 papers, h 4
  • Pu Li — 4 papers, h 4
  • Pu Li — 2 papers, h 4
  • Pu Li — 2 papers, h 3
  • Pu Li — 2 papers, h 19

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 citedGroup channel pruning and spatial attention distilling for object detection

17 citations · 19 across the 4 of their papers we have counts for

collaborators
Showing cs.CVShow all

4 papers · 1 filter

cs.CV2023

Mini-PointNetPlus: a local feature descriptor in deep learning model for 3d environment perception

Chuanyu Luo, Nuo Cheng, Sikun Ma +4

Common deep learning models for 3D environment perception often use pillarization/voxelization methods to convert point cloud data into pillars/voxels and then process it with a 2D…

cs.CV2023★ 1 cited

LEST: Large-scale LiDAR Semantic Segmentation with Transformer

Chuanyu Luo, Nuo Cheng, Sikun Ma +4

Large-scale LiDAR-based point cloud semantic segmentation is a critical task in autonomous driving perception. Almost all of the previous state-of-the-art LiDAR semantic segmentati…

cs.CV2023★ 17 cited

Group channel pruning and spatial attention distilling for object detection

Yun Chu, Pu Li, Yong Bai +3

Due to the over-parameterization of neural networks, many model compression methods based on pruning and quantization have emerged. They are remarkable in reducing the size, parame…

cs.CV2023★ 1 cited

Learning Knowledge-Rich Sequential Model for Planar Homography Estimation in Aerial Video

Pu Li, Xiaobai Liu

This paper presents an unsupervised approach that leverages raw aerial videos to learn to estimate planar homographic transformation between consecutive video frames. Previous lear…

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