Search Results for author: Cristina Vasconcelos

Found 8 papers, 4 papers with code

Blue noise for diffusion models

no code implementations7 Feb 2024 Xingchang Huang, Corentin Salaün, Cristina Vasconcelos, Christian Theobalt, Cengiz Öztireli, Gurprit Singh

In this paper, we introduce a novel and general class of diffusion models taking correlated noise within and across images into account.


CUF: Continuous Upsampling Filters

no code implementations CVPR 2023 Cristina Vasconcelos, Cengiz Oztireli, Mark Matthews, Milad Hashemi, Kevin Swersky, Andrea Tagliasacchi

Neural fields have rapidly been adopted for representing 3D signals, but their application to more classical 2D image-processing has been relatively limited.

Image Super-Resolution

Proper Reuse of Image Classification Features Improves Object Detection

1 code implementation CVPR 2022 Cristina Vasconcelos, Vighnesh Birodkar, Vincent Dumoulin

A common practice in transfer learning is to initialize the downstream model weights by pre-training on a data-abundant upstream task.

Classification Image Classification +4

Impact of Aliasing on Generalization in Deep Convolutional Networks

no code implementations ICCV 2021 Cristina Vasconcelos, Hugo Larochelle, Vincent Dumoulin, Rob Romijnders, Nicolas Le Roux, Ross Goroshin

We investigate the impact of aliasing on generalization in Deep Convolutional Networks and show that data augmentation schemes alone are unable to prevent it due to structural limitations in widely used architectures.

Data Augmentation Few-Shot Learning +1

Bridging the Gap Between Adversarial Robustness and Optimization Bias

1 code implementation17 Feb 2021 Fartash Faghri, Sven Gowal, Cristina Vasconcelos, David J. Fleet, Fabian Pedregosa, Nicolas Le Roux

We demonstrate that the choice of optimizer, neural network architecture, and regularizer significantly affect the adversarial robustness of linear neural networks, providing guarantees without the need for adversarial training.

Adversarial Robustness

An Effective Anti-Aliasing Approach for Residual Networks

no code implementations20 Nov 2020 Cristina Vasconcelos, Hugo Larochelle, Vincent Dumoulin, Nicolas Le Roux, Ross Goroshin

Image pre-processing in the frequency domain has traditionally played a vital role in computer vision and was even part of the standard pipeline in the early days of deep learning.

Few-Shot Learning Image Classification +1

Data Augmentation for Skin Lesion Analysis

1 code implementation5 Sep 2018 Fábio Perez, Cristina Vasconcelos, Sandra Avila, Eduardo Valle

In this work, we investigate the impact of 13 data augmentation scenarios for melanoma classification trained on three CNNs (Inception-v4, ResNet, and DenseNet).

Data Augmentation General Classification +2

Cannot find the paper you are looking for? You can Submit a new open access paper.