5 papers
Time-Series Foundation Model Embeddings for Remaining Useful Life Estimation
Amir El-Ghoussani, Michele De Vita, Ronald Naumann +1
Remaining Useful Life (RUL) prediction is essential for industrial predictive maintenance, yet many learning-based approaches rely on extensive feature engineering or large labeled…
Prompt-Guided Image Editing with Masked Logit Nudging in Visual Autoregressive Models
Amir El-Ghoussani, Marc Hölle, Gustavo Carneiro +1
We address the problem of prompt-guided image editing in visual autoregressive models. Given a source image and a target text prompt, we aim to modify the source image according to…
Visual Autoregressive Modelling for Monocular Depth Estimation
Amir El-Ghoussani, André Kaup, Nassir Navab +2
We propose a monocular depth estimation method based on visual autoregressive (VAR) priors, offering an alternative to diffusion-based approaches. Our method adapts a large-scale t…
Revisiting Gradient-based Uncertainty for Monocular Depth Estimation
Julia Hornauer, Amir El-Ghoussani, Vasileios Belagiannis
Monocular depth estimation, similar to other image-based tasks, is prone to erroneous predictions due to ambiguities in the image, for example, caused by dynamic objects or shadows…
Consistency Regularisation for Unsupervised Domain Adaptation in Monocular Depth Estimation
Amir El-Ghoussani, Julia Hornauer, Gustavo Carneiro +1
In monocular depth estimation, unsupervised domain adaptation has recently been explored to relax the dependence on large annotated image-based depth datasets. However, this comes…