collaborators

10 papers

cs.CV2026

QueryOcc: Query-based Self-Supervision for 3D Semantic Occupancy

Adam Lilja, Ji Lan, Junsheng Fu +1

Learning 3D scene geometry and semantics from images is a core challenge in computer vision and a key capability for autonomous driving. Since large-scale 3D annotation is prohibit…

cs.CV2026

Beyond Chamfer Distance: Granular Order-aware Evaluation Metric For Online Mapping

Chouaib Bencheikh Lehocine, Adam Lilja, Junsheng Fu +1

Online map estimation is a crucial component of autonomous driving systems that reduces the reliance on costly high-definition maps. State-of-the-art (SOTA) methods commonly predic…

cs.CG2026

Scalable GPU Construction of 3D Voronoi and Power Diagrams

Bernardo Taveira, Carl Lindström, Maryam Fatemi +2

Voronoi diagrams, and their more general weighted counterpart, power diagrams, are fundamental geometric constructs with wide-ranging applications. Recently, they have gained renew…

cs.CV2026

IDSplat: Instance-Decomposed 3D Gaussian Splatting for Driving Scenes

Carl Lindström, Mahan Rafidashti, Maryam Fatemi +3

Reconstructing dynamic driving scenes is essential for developing autonomous systems through sensor-realistic simulation. Although recent methods achieve high-fidelity reconstructi…

cs.CV2026

Semi-Supervised Hierarchical Open-Set Classification

Erik Wallin, Fredrik Kahl, Lars Hammarstrand

Hierarchical open-set classification handles previously unseen classes by assigning them to the most appropriate high-level category in a class taxonomy. We extend this paradigm to…

cs.LG2026

ProSub: Probabilistic Open-Set Semi-Supervised Learning with Subspace-Based Out-of-Distribution Detection

Erik Wallin, Lennart Svensson, Fredrik Kahl +1

In open-set semi-supervised learning (OSSL), we consider unlabeled datasets that may contain unknown classes. Existing OSSL methods often use the softmax confidence for classifying…