4 citations · 7 across the 7 of their papers we have counts for
8 papers
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…
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…
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…
Boosting Omnidirectional Stereo Matching with a Pre-trained Depth Foundation Model
Jannik Endres, Oliver Hahn, Charles Corbière +3
Omnidirectional depth perception is essential for mobile robotics applications that require scene understanding across a full 360° field of view. Camera-based setups offer a cost-e…
A Perspective on Deep Vision Performance with Standard Image and Video Codecs
Christoph Reich, Oliver Hahn, Daniel Cremers +2
Resource-constrained hardware, such as edge devices or cell phones, often rely on cloud servers to provide the required computational resources for inference in deep vision models.…
Boosting Unsupervised Semantic Segmentation with Principal Mask Proposals
Oliver Hahn, Nikita Araslanov, Simone Schaub-Meyer +1
Unsupervised semantic segmentation aims to automatically partition images into semantically meaningful regions by identifying global semantic categories within an image corpus with…