31 citations · 32 across the 15 of their papers we have counts for
6 papers · 2 filters
FedCKA: Representation-Guided Layer Personalization for Federated 3D Perception Across Driving Domains
Jolle Verhoog, Ali Burak Ünal, Holger Caesar
Robust perception in intelligent vehicles demands 3D object detectors that remain dependable under domain shifts, such as changes in time of day, location, or weather. However, due…
Does the VGGT Family Need All Its Layers?
Fengyi Zhang, Holger Caesar, Xiangyu Sun +3
Which layers of a feed-forward geometry model are needed to preserve both camera poses and dense 3D structure? We study layer redundancy in VGGT, , and VGGT-: 3,018 pruned…
SplatLabel: Pseudo-Labelling through 4D Gaussian Splatting
Nitya Nanvani, Andras Palffy, Holger Caesar
While 2D Vision Foundation Models offer a pathway to automate 3D semantic pseudo-labelling, translating these priors into robust 3D representations typically requires complex heuri…
Invaria: Learning Scale and Density Invariance in Point Clouds via Next-Resolution Prediction
Chun-Peng Chang, Shaoxiang Wang, Alain Pagani +2
Modern image encoders achieve high generalization by decoupling semantic meaning from resolution, an ability yet to be fully realized in the 3D domain. We investigate the failure o…
4DRC-OCC: Robust Semantic Occupancy Prediction Through Fusion of 4D Radar and Camera
David Ninfa, Andras Palffy, Holger Caesar
Autonomous driving requires robust perception across diverse environmental conditions, yet 3D semantic occupancy prediction remains challenging under adverse weather and lighting.…
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…