11 citations · 16 across the 10 of their papers we have counts for
10 papers
SparseFusion: Fusing Multi-Modal Sparse Representations for Multi-Sensor 3D Object Detection
Yichen Xie, Chenfeng Xu, Marie-Julie Rakotosaona +5
By identifying four important components of existing LiDAR-camera 3D object detection methods (LiDAR and camera candidates, transformation, and fusion outputs), we observe that all…
Quadric Representations for LiDAR Odometry, Mapping and Localization
Chao Xia, Chenfeng Xu, Patrick Rim +5
Current LiDAR odometry, mapping and localization methods leverage point-wise representations of 3D scenes and achieve high accuracy in autonomous driving tasks. However, the space-…
Active Finetuning: Exploiting Annotation Budget in the Pretraining-Finetuning Paradigm
Yichen Xie, Han Lu, Junchi Yan +3
Given the large-scale data and the high annotation cost, pretraining-finetuning becomes a popular paradigm in multiple computer vision tasks. Previous research has covered both the…
Editing Driver Character: Socially-Controllable Behavior Generation for Interactive Traffic Simulation
Wei-Jer Chang, Chen Tang, Chenran Li +3
Traffic simulation plays a crucial role in evaluating and improving autonomous driving planning systems. After being deployed on public roads, autonomous vehicles need to interact…
Analyzing and Enhancing Closed-loop Stability in Reactive Simulation
Wei-Jer Chang, Yeping Hu, Chenran Li +2
Simulation has played an important role in efficiently evaluating self-driving vehicles in terms of scalability. Existing methods mostly rely on heuristic-based simulation, where t…
What Matters for 3D Scene Flow Network
Guangming Wang, Yunzhe Hu, Zhe Liu +4
3D scene flow estimation from point clouds is a low-level 3D motion perception task in computer vision. Flow embedding is a commonly used technique in scene flow estimation, and it…