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Yan Gong

4 papers hereh-index 227 citations14 works total

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

author position
  • first author3
  • middle author1

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

fields
  • cs.CV3
  • cs.RO1
same name
  • Yan Gong — 20 papers, h 0
  • Yan Gong — 10 papers
  • Yan Gong — 10 papers, h 6
  • Yan Gong — 10 papers, h 5
  • Yan Gong — 7 papers, h 3
  • Yan Gong — 4 papers, h 9

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 citedProgressive Bird's Eye View Perception for Safety-Critical Autonomous Driving: A Comprehensive Survey

1 citations · 1 across the 4 of their papers we have counts for

collaborators

4 papers

cs.CV2025

DiffPixelFormer: Differential Pixel-Aware Transformer for RGB-D Indoor Scene Segmentation

Yan Gong, Jianli Lu, Yongsheng Gao +3

Indoor semantic segmentation is fundamental to computer vision and robotics, supporting applications such as autonomous navigation, augmented reality, and smart environments. Altho…

cs.RO2025★ 1 cited

Progressive Bird's Eye View Perception for Safety-Critical Autonomous Driving: A Comprehensive Survey

Yan Gong, Naibang Wang, Jianli Lu +13

Bird's-Eye-View (BEV) perception has become a foundational paradigm in autonomous driving, enabling unified spatial representations that support robust multi-sensor fusion and mult…

cs.CV2025

Stable at Any Speed: Speed-Driven Multi-Object Tracking with Learnable Kalman Filtering

Yan Gong, Mengjun Chen, Hao Liu +5

Multi-object tracking (MOT) enables autonomous vehicles to continuously perceive dynamic objects, supplying essential temporal cues for prediction, behavior understanding, and safe…

cs.CV2025

Collaborative Perception Datasets for Autonomous Driving: A Review

Naibang Wang, Deyong Shang, Yan Gong +6

Collaborative perception has attracted growing interest from academia and industry due to its potential to enhance perception accuracy, safety, and robustness in autonomous driving…

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