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20232026
most citedE2PNet: Event to Point Cloud Registration with Spatio-Temporal Representation Learning

4 citations · 9 across the 13 of their papers we have counts for

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7 papers · 1 filter

cs.CV2026

LEADER: Learning Reliable Local-to-Global Correspondences for LiDAR Relocalization

Jianshi Wu, Minghang Zhu, Dunqiang Liu +5

LiDAR relocalization has attracted increasing attention as it can deliver accurate 6-DoF pose estimation in complex 3D environments. Recent learning-based regression methods offer…

cs.CV2025

LightLoc: Learning Outdoor LiDAR Localization at Light Speed

Wen Li, Chen Liu, Shangshu Yu +5

Scene coordinate regression achieves impressive results in outdoor LiDAR localization but requires days of training. Since training needs to be repeated for each new scene, long tr…

cs.CV2025

L2RSI: Cross-view LiDAR-based Place Recognition for Large-scale Urban Scenes via Remote Sensing Imagery

Ziwei Shi, Xiaoran Zhang, Wenjing Xu +4

We tackle the challenge of LiDAR-based place recognition, which traditionally depends on costly and time-consuming prior 3D maps. To overcome this, we first construct LiRSI-XA data…

cs.CV2024

Mining and Transferring Feature-Geometry Coherence for Unsupervised Point Cloud Registration

Kezheng Xiong, Haoen Xiang, Qingshan Xu +4

Point cloud registration, a fundamental task in 3D vision, has achieved remarkable success with learning-based methods in outdoor environments. Unsupervised outdoor point cloud reg…

cs.CV2024

ConDo: Continual Domain Expansion for Absolute Pose Regression

Zijun Li, Zhipeng Cai, Bochun Yang +5

Visual localization is a fundamental machine learning problem. Absolute Pose Regression (APR) trains a scene-dependent model to efficiently map an input image to the camera pose in…

cs.CV2024

A New Adversarial Perspective for LiDAR-based 3D Object Detection

Shijun Zheng, Weiquan Liu, Yu Guo +3

Autonomous vehicles (AVs) rely on LiDAR sensors for environmental perception and decision-making in driving scenarios. However, ensuring the safety and reliability of AVs in comple…