Showing cs.CVShow all
3 papers · 1 filter
cs.CV2026
Evaluating Latent Generative Paradigms for High-Fidelity 3D Shape Completion from a Single Depth Image
Matthias Humt, Ulrich Hillenbrand, Rudolph Triebel
While generative models have seen significant adoption across a wide range of data modalities, including 3D data, a consensus on which model is best suited for which task has yet t…
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…