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Ya-Qin Zhang

4 papers here

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

author position
  • middle author1
  • last author3

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

fields
  • cs.CV3
  • cs.LG1
ORCID 0000-0003-1851-7932
same name
  • Ya-Qin Zhang — 16 papers, h 5
  • Ya-Qin Zhang — 15 papers, h 8
  • Ya-Qin Zhang — 9 papers, h 7
  • Ya-Qin Zhang — 7 papers, h 2
  • Ya-Qin Zhang — 7 papers, h 3
  • Ya-Qin Zhang — 6 papers, h 5

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 citedVIMI: Vehicle-Infrastructure Multi-view Intermediate Fusion for Camera-based 3D Object Detection

9 citations · 11 across the 4 of their papers we have counts for

collaborators

4 papers

cs.CV2023

DPF: Learning Dense Prediction Fields with Weak Supervision

Xiaoxue Chen, Yuhang Zheng, Yupeng Zheng +4

Nowadays, many visual scene understanding problems are addressed by dense prediction networks. But pixel-wise dense annotations are very expensive (e.g., for scene parsing) or impo…

cs.CV2023★ 9 cited

VIMI: Vehicle-Infrastructure Multi-view Intermediate Fusion for Camera-based 3D Object Detection

Zhe Wang, Siqi Fan, Xiaoliang Huo +5

In autonomous driving, Vehicle-Infrastructure Cooperative 3D Object Detection (VIC3D) makes use of multi-view cameras from both vehicles and traffic infrastructure, providing a glo…

cs.LG2023★ 2 cited

AdaptiveNet: Post-deployment Neural Architecture Adaptation for Diverse Edge Environments

Hao Wen, Yuanchun Li, Zunshuai Zhang +5

Deep learning models are increasingly deployed to edge devices for real-time applications. To ensure stable service quality across diverse edge environments, it is highly desirable…

cs.CV2023

LODE: Locally Conditioned Eikonal Implicit Scene Completion from Sparse LiDAR

Pengfei Li, Ruowen Zhao, Yongliang Shi +4

Scene completion refers to obtaining dense scene representation from an incomplete perception of complex 3D scenes. This helps robots detect multi-scale obstacles and analyse objec…

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