128 citations · 315 across the 51 of their papers we have counts for
6 papers · 1 filter
On the Impact of Hard Adversarial Instances on Overfitting in Adversarial Training
Chen Liu, Zhichao Huang, Mathieu Salzmann +2
Adversarial training is a popular method to robustify models against adversarial attacks. However, it exhibits much more severe overfitting than training on clean inputs. In this w…
Optimizing Latent Space Directions For GAN-based Local Image Editing
Ehsan Pajouheshgar, Tong Zhang, Sabine Süsstrunk
Generative Adversarial Network (GAN) based localized image editing can suffer from ambiguity between semantic attributes. We thus present a novel objective function to evaluate the…
Estimating Image Depth in the Comics Domain
Deblina Bhattacharjee, Martin Everaert, Mathieu Salzmann +1
Estimating the depth of comics images is challenging as such images a) are monocular; b) lack ground-truth depth annotations; c) differ across different artistic styles; d) are spa…
Fidelity Estimation Improves Noisy-Image Classification With Pretrained Networks
Xiaoyu Lin, Deblina Bhattacharjee, Majed El Helou +1
Image classification has significantly improved using deep learning. This is mainly due to convolutional neural networks (CNNs) that are capable of learning rich feature extractors…
Modeling Object Dissimilarity for Deep Saliency Prediction
Bahar Aydemir, Deblina Bhattacharjee, Tong Zhang +3
Saliency prediction has made great strides over the past two decades, with current techniques modeling low-level information, such as color, intensity and size contrasts, and high-…
Deep Gaussian Denoiser Epistemic Uncertainty and Decoupled Dual-Attention Fusion
Xiaoqi Ma, Xiaoyu Lin, Majed El Helou +1
Following the performance breakthrough of denoising networks, improvements have come chiefly through novel architecture designs and increased depth. While novel denoising networks…