Publications associées à DALL-E

VETIM: Expanding the Vocabulary of Text-to-Image Models only with Text

Sabine Süsstrunk, Radhakrishna Achanta, Mahmut Sami Arpa, Martin Nicolas Everaert

Text-to-image models, such as Stable Diffusion, can generate high-quality images from simple textual prompts. With methods such as Textual Inversion, it is possible to expand the vocabulary of these models with additional concepts, by learning the vocabula ...

BMVA2023

Toward responsible face datasets: modeling the distribution of a disentangled latent space for sampling face images from demographic groups

Sébastien Marcel, Parsa Rahimi Noshanagh, Christophe René Joseph Ecabert

Recently, it has been exposed that some modern facial recognition systems could discriminate specific demographic groups and may lead to unfair attention with respect to various facial attributes such as gender and origin. The main reason are the biases in ...

IEEE2023

ChatGPT takes on the European Exam in Core Cardiology: an artificial intelligence success story?

Emmanuel Abbé, Olivier Muller, Thabodhan Mahendiran, Stéphane Fournier

Chat Generative Pre-trained Transformer (ChatGPT) is currently a trending topic worldwide triggering extensive debate about its predictive power, its potential uses, and its wider implications. Recent publications have demonstrated that ChatGPT can correct ...

Oxford2023

3DHumanGAN: 3D-Aware Human Image Generation with 3D Pose Mapping

Zhuoqian Yang, Siyuan Li

We present 3DHumanGAN, a 3D-aware generative adversarial network that synthesizes photo-like images of fullbody humans with consistent appearances under different view-angles and body-poses. To tackle the representational and computational challenges in sy ...

Ieee Computer Soc2023

OptTTA: Learnable Test-Time Augmentation for Source-Free Medical Image Segmentation Under Domain Shift

Jean-Philippe Thiran, Guillaume Marc Georges Vray, Devavrat Tomar

As distribution shifts are inescapable in realistic clinical scenarios due to inconsistencies in imaging protocols, scanner vendors, and across different centers, well-trained deep models incur a domain generalization problem in unseen environments. Despit ...

PMLR2022

MultiMAE: Multi-modal Multi-task Masked Autoencoders

Amir Roshan Zamir, Roman Christian Bachmann, David Mizrahi, Andrei Atanov

We propose a pre-training strategy called Multi-modal Multi-task Masked Autoencoders (MultiMAE). It differs from standard Masked Autoencoding in two key aspects: I) it can optionally accept additional modalities of information in the input besides the RGB ...

SPRINGER INTERNATIONAL PUBLISHING AG2022

Self-supervised Segmentation via Background Inpainting

Pascal Fua, Mathieu Salzmann, Isinsu Katircioglu, Helge Jochen Rhodin, Victor Constantin

While supervised object detection and segmentation methods achieve impressive accuracy, they generalize poorly to images whose appearance significantly differs from the data they have been trained on. To address this when annotating data is prohibitively e ...

2022

Overcoming Multi-model Forgetting

Mathieu Salzmann, Anthony Christopher Davison, Martin Jaggi, Yassine Benyahia, Claudiu-Cristian Musat, Kaicheng Yu

We identify a phenomenon, which we refer to as multi-model forgetting, that occurs when sequentially training multiple deep networks with partially-shared parameters; the performance of previously-trained models degrades as one optimizes a subsequent one, ...

JMLR2019

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DALL-E

VETIM: Expanding the Vocabulary of Text-to-Image Models only with Text

Toward responsible face datasets: modeling the distribution of a disentangled latent space for sampling face images from demographic groups

ChatGPT takes on the European Exam in Core Cardiology: an artificial intelligence success story?

3DHumanGAN: 3D-Aware Human Image Generation with 3D Pose Mapping

OptTTA: Learnable Test-Time Augmentation for Source-Free Medical Image Segmentation Under Domain Shift

MultiMAE: Multi-modal Multi-task Masked Autoencoders

Predicting emotional response to visual stimuli, a machine learning approach

Self-supervised Segmentation via Background Inpainting

Self-Supervision By Prediction For Object Discovery In Videos

Overcoming Multi-model Forgetting

Graph Chatbot

Chattez avec Graph Search

3DHumanGAN: 3D-Aware Human Image Generation with 3D Pose Mapping

Toward responsible face datasets: modeling the distribution of a disentangled latent space for sampling face images from demographic groups

OptTTA: Learnable Test-Time Augmentation for Source-Free Medical Image Segmentation Under Domain Shift

MultiMAE: Multi-modal Multi-task Masked Autoencoders

Predicting emotional response to visual stimuli, a machine learning approach

Self-supervised Segmentation via Background Inpainting

Overcoming Multi-model Forgetting

ChatGPT takes on the European Exam in Core Cardiology: an artificial intelligence success story?