Nov 24, 2017 · We develop a novel feature attribution technique based on Wasserstein Generative Adversarial Networks (WGAN), which does not suffer from this limitation.

Attributing the pixels of an input image to a certain cate- gory is an important and well-studied problem in computer vision, with applications ranging from ...

This repository contains the code to reproduce results for the paper cited above, where the authors presents a novel feature attribution technique based on ...

Attributing the pixels of an input image to a certain cate- gory is an important and well-studied problem in computer vision, with applications ranging from ...

Baumgartner et al. proposed VAGAN, a GAN-based visual feature attribution technology [11] for weakly supervised localisation. It uses Wasserstein GAN [8] as a ...

We develop a novel feature attribution technique based on Wasserstein Generative Adversarial Networks (WGAN), which does not suffer from this limitation.

Jan 25, 2024 · We show that our proposed method performs substantially better than the state-of-the-art for visual attribution on a synthetic dataset and on ...

In this section we describe the exact network architec- tures used for the 3D VA-GAN. We present the critic and map generator functions as Python-inspired ...

Nov 24, 2017 · This paper develops a novel feature attribution technique based on Wasserstein Generative Adversarial Networks (WGAN), which performs substantially better

Visual feature attribution using Wasserstein GANs. Mendeley · CSV · RIS · BibTeX ; Date. 2018 ; Type. Conference Paper ; Publication status. published ; Book title.