2 citations · 2 across the 7 of their papers we have counts for
9 papers · 1 filter
Doppio: A Dataset for Contactless Weight Estimation of Falling Particles
Simon Kiefhaber, Jan-Martin O. Steitz, Julia Grabinski +5
Measuring the mass of powder, including falling particles, is a common task in industrial applications. While scales are effective for static measurements, many applications requir…
Contrastive Energy Fields for Inference-Time Procedure Planning in Instructional Videos
Mohamed Afham, Christoph Reich, Oliver Hahn +2
Procedure planning seeks to estimate a sequence of actions to transition from an observed initial state to a given goal state. Current procedure planning approaches directly predic…
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…
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…
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)…
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…
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…
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…
Scene-Centric Unsupervised Panoptic Segmentation
Oliver Hahn, Christoph Reich, Nikita Araslanov +3
Unsupervised panoptic segmentation aims to partition an image into semantically meaningful regions and distinct object instances without training on manually annotated data. In con…