activity
20212023
most citedCRLF: Automatic Calibration and Refinement based on Line Feature for LiDAR and Camera in Road Scenes

28 citations · 40 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CV2023

COOLer: Class-Incremental Learning for Appearance-Based Multiple Object Tracking

Zhizheng Liu, Mattia Segu, Fisher Yu

Continual learning allows a model to learn multiple tasks sequentially while retaining the old knowledge without the training data of the preceding tasks. This paper extends the sc…

cs.CV20221 cited

3D Textured Shape Recovery with Learned Geometric Priors

Lei Li, Zhizheng Liu, Weining Ren +4

3D textured shape recovery from partial scans is crucial for many real-world applications. Existing approaches have demonstrated the efficacy of implicit function representation, b…

cs.RO20221 cited

OpenCalib: A Multi-sensor Calibration Toolbox for Autonomous Driving

Guohang Yan, Liu Zhuochun, Chengjie Wang +10

Accurate sensor calibration is a prerequisite for multi-sensor perception and localization systems for autonomous vehicles. The intrinsic parameter calibration of the sensor is to…

cs.RO202110 cited

Perception Entropy: A Metric for Multiple Sensors Configuration Evaluation and Design

Tao Ma, Zhizheng Liu, Yikang Li

Sensor configuration, including the sensor selections and their installation locations, serves a crucial role in autonomous driving. A well-designed sensor configuration significan…

cs.CV202128 cited

CRLF: Automatic Calibration and Refinement based on Line Feature for LiDAR and Camera in Road Scenes

Tao Ma, Zhizheng Liu, Guohang Yan +1

For autonomous vehicles, an accurate calibration for LiDAR and camera is a prerequisite for multi-sensor perception systems. However, existing calibration techniques require either…