By reinterpreting a robust discriminative classifier as Energy-based Model (EBM), we offer a
new take on the dynamics of adversarial training (AT). Our analysis of the energy landscape …

Abstract Test Time Adaptation (TTA) is a pivotal concept in machine learning, enabling
models to perform well in real-world scenarios, where test data distribution differs from …

Generative image editing has recently witnessed extremely fast-paced growth. Some works
use high-level conditioning such as text while others use low-level conditioning …

Editing High Dynamic Range (HDR) environment maps using an inverse differentiable
rendering architecture is a complex inverse problem due to the sparsity of relevant pixels …

We offer a study that connects robust discriminative classifiers trained with adversarial
training (AT) with generative modeling in the form of Energy-based Models (EBM). We do so …

Mechrez et al.[6] proposed the Contextual loss for image transformation with non-aligned
data. Heitz et al.[5] proved it unsuitable for texture synthesis but didn't analyze why. In this …