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researcher

Li Zhang

12 papers hereh-index 8341 citations14 works total

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

author position
  • middle author2
  • last author10

Across the 12 of 12 papers where every author was matched, so the position is known.

fields
  • cs.CV10
  • cs.AI1
  • eess.IV1
same name
  • Li Zhang — 41 papers, h 10
  • Li Zhang — 37 papers, h 42
  • Li Zhang — 24 papers, h 13
  • Li Zhang — 21 papers, h 6
  • Li Zhang — 20 papers, h 20
  • Li Zhang — 19 papers, h 16

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
most citedFrom Summary to Action: Enhancing Large Language Models for Complex Tasks with Open World APIs

3 citations · 5 across the 11 of their papers we have counts for

collaborators
Showing 2024 · cs.CVShow all

4 papers · 2 filters

cs.CV2024

LaneCorrect: Self-supervised Lane Detection

Ming Nie, Xinyue Cai, Hang Xu +1

Lane detection has evolved highly functional autonomous driving system to understand driving scenes even under complex environments. In this paper, we work towards developing a gen…

cs.CV2024

OpenOcc: Open Vocabulary 3D Scene Reconstruction via Occupancy Representation

Haochen Jiang, Yueming Xu, Yihan Zeng +4

3D reconstruction has been widely used in autonomous navigation fields of mobile robotics. However, the former research can only provide the basic geometry structure without the ca…

cs.CV2024

LaneGraph2Seq: Lane Topology Extraction with Language Model via Vertex-Edge Encoding and Connectivity Enhancement

Renyuan Peng, Xinyue Cai, Hang Xu +4

Understanding road structures is crucial for autonomous driving. Intricate road structures are often depicted using lane graphs, which include centerline curves and connections for…

cs.CV2024

Translating Images to Road Network: A Sequence-to-Sequence Perspective

Jiachen Lu, Ming Nie, Bozhou Zhang +6

The extraction of road network is essential for the generation of high-definition maps since it enables the precise localization of road landmarks and their interconnections. Howev…

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