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Xin Huang

4 papers hereh-index 3135 citations5 works total

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.CV2
  • cs.AI1
  • cs.LG1
same name
  • Xin Huang — 17 papers, h 13
  • Xin Huang — 12 papers, h 23
  • Xin Huang — 12 papers, h 4
  • Xin Huang — 11 papers, h 10
  • Xin Huang — 10 papers, h 7
  • Xin Huang — 9 papers, h 11

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 citedVLM-AD: End-to-End Autonomous Driving through Vision-Language Model Supervision

1 citations · 2 across the 4 of their papers we have counts for

collaborators

4 papers

cs.AI2024

Causal Composition Diffusion Model for Closed-loop Traffic Generation

Haohong Lin, Xin Huang, Tung Phan-Minh +6

Simulation is critical for safety evaluation in autonomous driving, particularly in capturing complex interactive behaviors. However, generating realistic and controllable traffic…

cs.CV2024★ 1 cited

VLM-AD: End-to-End Autonomous Driving through Vision-Language Model Supervision

Yi Xu, Yuxin Hu, Zaiwei Zhang +5

Human drivers rely on commonsense reasoning to navigate diverse and dynamic real-world scenarios. Existing end-to-end (E2E) autonomous driving (AD) models are typically optimized t…

cs.LG2024★ 1 cited

DriveGPT: Scaling Autoregressive Behavior Models for Driving

Xin Huang, Eric M. Wolff, Paul Vernaza +13

We present DriveGPT, a scalable behavior model for autonomous driving. We model driving as a sequential decision-making task, and learn a transformer model to predict future agent…

cs.CV2024

Cohere3D: Exploiting Temporal Coherence for Unsupervised Representation Learning of Vision-based Autonomous Driving

Yichen Xie, Hongge Chen, Gregory P. Meyer +6

Due to the lack of depth cues in images, multi-frame inputs are important for the success of vision-based perception, prediction, and planning in autonomous driving. Observations f…

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