collaborators

7 papers

cs.CV2026

MAGneT-3D: Monocular and Domain-Generalizable Temporal 3D Detection

Mohamed Kotb, Johannes Meier, Christoph Reich +3

Monocular temporal 3D detection aims to detect objects in 3D, given a monocular video. Query-based 3D detectors unify detection and cross-view association, but their learnable quer…

cs.CV2026

LeAD-M3D: Leveraging Asymmetric Distillation for Real-Time Monocular 3D Detection

Johannes Meier, Jonathan Michel, Oussema Dhaouadi +7

Real-time monocular 3D object detection remains challenging due to severe depth ambiguity, viewpoint shifts, and the high computational cost of 3D reasoning. Existing approaches ei…

cs.CV2026

Scene-Centric Unsupervised Video Panoptic Segmentation

Christoph Reich, Oliver Hahn, Nikita Araslanov +4

Video panoptic segmentation (VPS) aims to jointly detect, segment, and track all objects while partitioning the video into semantically consistent regions. We introduce the task se…

cs.CV2026

INSID3: Training-Free In-Context Segmentation with DINOv3

Claudia Cuttano, Gabriele Trivigno, Christoph Reich +3

In-context segmentation (ICS) aims to segment arbitrary concepts, e.g., objects, parts, or personalized instances, given one annotated visual examples. Existing work relies on (i)…

cs.CV2025

Motion-Refined DINOSAUR for Unsupervised Multi-Object Discovery

Xinrui Gong, Oliver Hahn, Christoph Reich +4

Unsupervised multi-object discovery (MOD) aims to detect and localize distinct object instances in visual scenes without any form of human supervision. Recent approaches leverage o…

cs.CV2025

Feed-Forward SceneDINO for Unsupervised Semantic Scene Completion

Aleksandar Jevtić, Christoph Reich, Felix Wimbauer +4

Semantic scene completion (SSC) aims to infer both the 3D geometry and semantics of a scene from single images. In contrast to prior work on SSC that heavily relies on expensive gr…