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researcher

Yu Ma

4 papers hereh-index 11 citations3 works total

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

author position
  • first author2
  • middle author2

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

fields
  • cs.CV4
same name
  • Yu Ma — 22 papers, h 9
  • Yu Ma — 10 papers, h 4
  • Yu Ma — 8 papers, h 7
  • Yu Ma — 5 papers, h 3
  • Yu Ma — 4 papers, h 2
  • Yu Ma — 4 papers, h 2

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
20182026
most citedAugmented LiDAR Simulator for Autonomous Driving

168 citations · 168 across the 3 of their papers we have counts for

collaborators

4 papers

cs.CV2026

The Midas Touch for Metric Depth: Interpretable Metricization for Generalizable Depth Perception

Mengtan Zhang, Yu Ma, Shiqi Jiang +6

Recent foundation models have drastically improved the generalization of monocular relative depth estimation, yet recovering accurate metric depth from their estimates for depth pe…

cs.CV2026

The Midas Touch for Metric Depth

Yu Ma, Zizhan Guo, Zuyi Xiong +5

Recent advances have markedly improved the cross-scene generalization of relative depth estimation, yet its practical applicability remains limited by the absence of metric scale,…

cs.CV2025

HBSplat: Robust Sparse-View Gaussian Reconstruction with Hybrid-Loss Guided Depth and Bidirectional Warping

Yu Ma, Guoliang Wei, Haihong Xiao +1

Novel View Synthesis (NVS) from sparse views presents a formidable challenge in 3D reconstruction, where limited multi-view constraints lead to severe overfitting, geometric distor…

cs.CV2018★ 168 cited

Augmented LiDAR Simulator for Autonomous Driving

Jin Fang, Dingfu Zhou, Feilong Yan +5

In Autonomous Driving (AD), detection and tracking of obstacles on the roads is a critical task. Deep-learning based methods using annotated LiDAR data have been the most widely ad…

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