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Li Liu

2 papers hereh-index 457 citations5 works total

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

author position
  • middle author2

Across the 2 of 2 papers where every author was matched, so the position is known.

fields
  • cs.CV2
same name
  • Li Liu — 11 papers, h 8
  • Li Liu — 10 papers, h 10
  • Li Liu — 6 papers, h 5
  • Li Liu — 5 papers, h 2
  • Li Liu — 5 papers, h 2
  • Li Liu — 5 papers, h 4

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 citedDepthMaster: Taming Diffusion Models for Monocular Depth Estimation

5 citations · 5 across the 2 of their papers we have counts for

collaborators
Showing cs.CVShow all

4 papers · 1 filter

cs.CV2026★ 5 cited

DepthMaster: Taming Diffusion Models for Monocular Depth Estimation

Ziyang Song, Zerong Wang, Bo Li +5

Monocular depth estimation within the diffusion-denoising paradigm demonstrates impressive generalization ability but suffers from low inference speed. Recent methods adopt a singl…

cs.CV2026

GLASS: Geometry-aware Local Alignment and Structure Synchronization Network for 2D-3D Registration

Zhixin Cheng, Jiacheng Deng, Xinjun Li +5

Image-to-point cloud registration methods typically follow a coarse-to-fine pipeline, extracting patch-level correspondences and refining them into dense pixel-to-point matches. Ho…

cs.CV2024

Plane2Depth: Hierarchical Adaptive Plane Guidance for Monocular Depth Estimation

Li Liu, Ruijie Zhu, Jiacheng Deng +3

Monocular depth estimation aims to infer a dense depth map from a single image, which is a fundamental and prevalent task in computer vision. Many previous works have shown impress…

cs.CV2024

ScaleDepth: Decomposing Metric Depth Estimation into Scale Prediction and Relative Depth Estimation

Ruijie Zhu, Chuxin Wang, Ziyang Song +3

Estimating depth from a single image is a challenging visual task. Compared to relative depth estimation, metric depth estimation attracts more attention due to its practical physi…

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