17 citations · 22 across the 8 of their papers we have counts for
8 papers
3DGS-Calib: 3D Gaussian Splatting for Multimodal SpatioTemporal Calibration
Quentin Herau, Moussab Bennehar, Arthur Moreau +6
Reliable multimodal sensor fusion algorithms require accurate spatiotemporal calibration. Recently, targetless calibration techniques based on implicit neural representations have…
SWinGS: Sliding Windows for Dynamic 3D Gaussian Splatting
Richard Shaw, Michal Nazarczuk, Jifei Song +4
Novel view synthesis has shown rapid progress recently, with methods capable of producing increasingly photorealistic results. 3D Gaussian Splatting has emerged as a promising meth…
HeadGaS: Real-Time Animatable Head Avatars via 3D Gaussian Splatting
Helisa Dhamo, Yinyu Nie, Arthur Moreau +4
3D head animation has seen major quality and runtime improvements over the last few years, particularly empowered by the advances in differentiable rendering and neural radiance fi…
Human Gaussian Splatting: Real-time Rendering of Animatable Avatars
Arthur Moreau, Jifei Song, Helisa Dhamo +3
This work addresses the problem of real-time rendering of photorealistic human body avatars learned from multi-view videos. While the classical approaches to model and render virtu…
CROSSFIRE: Camera Relocalization On Self-Supervised Features from an Implicit Representation
Arthur Moreau, Nathan Piasco, Moussab Bennehar +3
Beyond novel view synthesis, Neural Radiance Fields are useful for applications that interact with the real world. In this paper, we use them as an implicit map of a given scene an…
ImPosing: Implicit Pose Encoding for Efficient Visual Localization
Arthur Moreau, Thomas Gilles, Nathan Piasco +3
We propose a novel learning-based formulation for visual localization of vehicles that can operate in real-time in city-scale environments. Visual localization algorithms determine…
LENS: Localization enhanced by NeRF synthesis
Arthur Moreau, Nathan Piasco, Dzmitry Tsishkou +2
Neural Radiance Fields (NeRF) have recently demonstrated photo-realistic results for the task of novel view synthesis. In this paper, we propose to apply novel view synthesis to th…
CoordiNet: uncertainty-aware pose regressor for reliable vehicle localization
Arthur Moreau, Nathan Piasco, Dzmitry Tsishkou +2
In this paper, we investigate visual-based camera re-localization with neural networks for robotics and autonomous vehicles applications. Our solution is a CNN-based algorithm whic…