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cs.CV2026
Finding NeMO: A Geometry-Aware Representation of Template Views for Few-Shot Perception
Sebastian Jung, Leonard Klüpfel, Rudolph Triebel +1
We present Neural Memory Object (NeMO), a novel object-centric representation that can be used to detect, segment and estimate the 6DoF pose of objects unseen during training using…
cs.CV2025
Conditional Latent Diffusion Models for Zero-Shot Instance Segmentation
Maximilian Ulmer, Wout Boerdijk, Rudolph Triebel +1
This paper presents OC-DiT, a novel class of diffusion models designed for object-centric prediction, and applies it to zero-shot instance segmentation. We propose a conditional la…
cs.CV2024
How Important are Data Augmentations to Close the Domain Gap for Object Detection in Orbit?
Maximilian Ulmer, Leonard Klüpfel, Maximilian Durner +1
We investigate the efficacy of data augmentations to close the domain gap in spaceborne computer vision, crucial for autonomous operations like on-orbit servicing. As the use of co…