activity
20152026
most citedIntrinsic Motivation and Mental Replay enable Efficient Online Adaptation in Stochastic Recurrent Networks

23 citations · 92 across the 32 of their papers we have counts for

collaborators

35 papers

cs.RO2026

InfiNoVA: Infinite Novel View Augmentation for Viewpoint Invariant Robot Policies

Sai Puneeth Reddy Gottam, Elmar Rueckert, Vedant Dave

Vision-Language-Action (VLA) policies often rely strongly on the camera viewpoints seen during training, causing substantial performance degradation when deployed from unseen persp…

cs.CV2026

Pro-Bench: Prompt-Robust Open-Vocabulary Visual Grounding Across Real-World Heterogeneous Environments

Linus Nwankwo, Muslim Alaran, Christian Rauch +2

Open-vocabulary visual grounding enables robots to localise task-relevant entities from natural-language queries without dependence on predefined perceptual taxonomies. However, ex…

cs.RO2026

Sandwich-Residuals: Parameter-Efficient Test-time Adaptation of World Models

Krishnam Soni, Aditya Sehgal, Vedant Dave +1

Latent world models enable planning by predicting the effects of actions in a learned representation space, but their predictions can become unreliable when test-time conditions di…

cs.CV2026

EliGSiR: Continual RGB-D Mapping with Gaussian Splatting under Bounded Compute

Björn Ellensohn, Elmar Rueckert, Christian Rauch

Conventional 3D Gaussian Splatting assumes a closed set of observations and long optimization schedules. Continual RGB-D mapping in contrast poses the problem that new observations…

cs.RO2026

SteelDS: A High-Resolution Video Dataset of E40 Steel Scrap for Object Detection and Instance Segmentation

Melanie Neubauer, Christian Rauch, Gerald Koinig +3

This dataset provides high-resolution, annotated video sequences of shredded E40-grade steel and copper scrap on a conveyor belt. Captured in a controlled laboratory environment, t…

cs.CV2026

PASTA: Vision Transformer Patch Aggregation for Weakly Supervised Target and Anomaly Segmentation

Melanie Neubauer, Elmar Rueckert, Christian Rauch

Detecting unseen anomalies in unstructured environments presents a critical challenge for industrial and agricultural applications such as material recycling and weeding. Existing…