5 citations · 6 across the 5 of their papers we have counts for
6 papers
Task-conditioned adaptation of visual features in multi-task policy learning
Pierre Marza, Laetitia Matignon, Olivier Simonin +1
Successfully addressing a wide variety of tasks is a core ability of autonomous agents, requiring flexibly adapting the underlying decision-making strategies and, as we argue in th…
AutoNeRF: Training Implicit Scene Representations with Autonomous Agents
Pierre Marza, Laetitia Matignon, Olivier Simonin +3
Implicit representations such as Neural Radiance Fields (NeRF) have been shown to be very effective at novel view synthesis. However, these models typically require manual and care…
Multi-Object Navigation with dynamically learned neural implicit representations
Pierre Marza, Laetitia Matignon, Olivier Simonin +1
Understanding and mapping a new environment are core abilities of any autonomously navigating agent. While classical robotics usually estimates maps in a stand-alone manner with SL…
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…
Teaching Agents how to Map: Spatial Reasoning for Multi-Object Navigation
Pierre Marza, Laetitia Matignon, Olivier Simonin +1
In the context of visual navigation, the capacity to map a novel environment is necessary for an agent to exploit its observation history in the considered place and efficiently re…
DeepLPF: Deep Local Parametric Filters for Image Enhancement
Sean Moran, Pierre Marza, Steven McDonagh +2
Digital artists often improve the aesthetic quality of digital photographs through manual retouching. Beyond global adjustments, professional image editing programs provide local a…