12 citations · 31 across the 10 of their papers we have counts for
17 papers · 1 filter
End-to-End (Instance)-Image Goal Navigation through Correspondence as an Emergent Phenomenon
Guillaume Bono, Leonid Antsfeld, Boris Chidlovskii +2
Most recent work in goal oriented visual navigation resorts to large-scale machine learning in simulated environments. The main challenge lies in learning compact representations g…
Satellite Image Semantic Segmentation
Eric Guérin, Killian Oechslin, Christian Wolf +1
In this paper, we propose a method for the automatic semantic segmentation of satellite images into six classes (sparse forest, dense forest, moor, herbaceous formation, building,…
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…
Universal Domain Adaptation in Ordinal Regression
Boris Chidlovskii, Assem Sadek, Christian Wolf
We address the problem of universal domain adaptation (UDA) in ordinal regression (OR), which attempts to solve classification problems in which labels are not independent, but fol…
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,…