activity
20182026
most citedSee Further Than CFAR: a Data-Driven Radar Detector Trained by Lidar

15 citations · 47 across the 24 of their papers we have counts for

collaborators

29 papers

cs.CV2026

OpenCVL: An Open, Diverse, and Large-Scale Dataset for Fine-Grained Cross-View Localization

Zimin Xia, Mubariz Zaffar, Junsheng Fu +2

Fine-grained Cross-View Localization (CVL) estimates the precise position and orientation of a ground-level image by aligning it with geo-referenced aerial imagery, offering a scal…

cs.CV2026

RVLoss: Runoff Vote Loss for Self-Supervised LiDAR Scene Flow Estimation

Shiming Wang, Liangliang Nan, Julian Kooij +2

LiDAR scene flow estimates point-wise motion between two consecutive scans, referred to as the source and target. Leading self-supervised methods typically minimize the Chamfer los…

cs.CV2026

Emergent 3D Instance Segmentation from Self-Supervised Point Transformers

Ted Lentsch, Santiago Montiel-Marín, Holger Caesar +1

Unsupervised 3D instance segmentation of outdoor LiDAR scans has traditionally relied on handcrafted geometric priors such as density-based clustering, motion cues, or projected 2D…

cs.RO2026

COP-Q: Safety-First Reinforcement Learning for Robot Control via Cholesky-Ordered Projection

Guopeng Li, Moritz A. Zanger, Matthijs T. J. Spaan +1

Safe robot control requires maximizing return while satisfying safety constraints. In off-policy safe reinforcement learning, reward and safety Q-values are commonly learned by sep…

cs.LG2026

Off-Policy Safe Reinforcement Learning with Constrained Optimistic Exploration

Guopeng Li, Matthijs T. J. Spaan, Julian F. P. Kooij

When safety is formulated as a limit of cumulative cost, safe reinforcement learning (RL) aims to learn policies that maximize return subject to the cost constraint in data collect…

cs.CV2026

AsyncBEV: Cross-modal Flow Alignment in Asynchronous 3D Object Detection

Shiming Wang, Holger Caesar, Liangliang Nan +1

In autonomous driving, multi-modal perception tasks like 3D object detection typically rely on well-synchronized sensors, both at training and inference. However, despite the use o…