44 citations · 66 across the 7 of their papers we have counts for
10 papers
An experimental study of the vision-bottleneck in VQA
Pierre Marza, Corentin Kervadec, Grigory Antipov +2
As in many tasks combining vision and language, both modalities play a crucial role in Visual Question Answering (VQA). To properly solve the task, a given model should both unders…
Are E2E ASR models ready for an industrial usage?
Valentin Vielzeuf, Grigory Antipov
The Automated Speech Recognition (ASR) community experiences a major turning point with the rise of the fully-neural (End-to-End, E2E) approaches. At the same time, the conventiona…
Supervising the Transfer of Reasoning Patterns in VQA
Corentin Kervadec, Christian Wolf, Grigory Antipov +2
Methods for Visual Question Anwering (VQA) are notorious for leveraging dataset biases rather than performing reasoning, hindering generalization. It has been recently shown that b…
How Transferable are Reasoning Patterns in VQA?
Corentin Kervadec, Theo Jaunet, Grigory Antipov +3
Since its inception, Visual Question Answering (VQA) is notoriously known as a task, where models are prone to exploit biases in datasets to find shortcuts instead of performing hi…
VisQA: X-raying Vision and Language Reasoning in Transformers
Theo Jaunet, Corentin Kervadec, Romain Vuillemot +3
Visual Question Answering systems target answering open-ended textual questions given input images. They are a testbed for learning high-level reasoning with a primary use in HCI,…
Automatic Quality Assessment for Audio-Visual Verification Systems. The LOVe submission to NIST SRE Challenge 2019
Grigory Antipov, Nicolas Gengembre, Olivier Le Blouch +1
Fusion of scores is a cornerstone of multimodal biometric systems composed of independent unimodal parts. In this work, we focus on quality-dependent fusion for speaker-face verifi…
Estimating semantic structure for the VQA answer space
Corentin Kervadec, Grigory Antipov, Moez Baccouche +1
Since its appearance, Visual Question Answering (VQA, i.e. answering a question posed over an image), has always been treated as a classification problem over a set of predefined a…
Roses Are Red, Violets Are Blue... but Should Vqa Expect Them To?
Corentin Kervadec, Grigory Antipov, Moez Baccouche +1
Models for Visual Question Answering (VQA) are notorious for their tendency to rely on dataset biases, as the large and unbalanced diversity of questions and concepts involved and…
Weak Supervision helps Emergence of Word-Object Alignment and improves Vision-Language Tasks
Corentin Kervadec, Grigory Antipov, Moez Baccouche +1
The large adoption of the self-attention (i.e. transformer model) and BERT-like training principles has recently resulted in a number of high performing models on a large panoply o…
Face Aging With Conditional Generative Adversarial Networks
Grigory Antipov, Moez Baccouche, Jean-Luc Dugelay
It has been recently shown that Generative Adversarial Networks (GANs) can produce synthetic images of exceptional visual fidelity. In this work, we propose the GAN-based method fo…