41 citations · 42 across the 5 of their papers we have counts for
6 papers
Diffusable Latents from Structure-Agnostic Distillation
Adrien Ramanana Rahary, Nicolas Dufour, Patrick Pérez +1
Distilling pretrained foundation models into an autoencoder bottleneck improves latent diffusability, enabling diffusion models to converge faster and reach higher sample quality.…
Multiplayer Interactive World Models with Representation Autoencoders
Anthony Hu, Václav Volhejn, Adrien Ramanana Rahary +24
We introduce the first multiplayer world model for highly dynamic environments governed by complex physical interactions. Whereas single-player world models treat the other agents…
One View Is Enough: In-the-Wild Monocular Pretraining for Novel View Generation
Adrien Ramanana Rahary, Nicolas Dufour, Patrick Perez +1
Monocular novel-view synthesis has long required multi-view image pairs for supervision, limiting training to a narrow set of purpose-built datasets. We propose in-the-wild monocul…
PointBeV: A Sparse Approach to BeV Predictions
Loick Chambon, Eloi Zablocki, Mickael Chen +3
Bird's-eye View (BeV) representations have emerged as the de-facto shared space in driving applications, offering a unified space for sensor data fusion and supporting various down…
ToddlerDiffusion: Interactive Structured Image Generation with Cascaded Schrödinger Bridge
Eslam Abdelrahman, Liangbing Zhao, Vincent Tao Hu +3
Diffusion models break down the challenging task of generating data from high-dimensional distributions into a series of easier denoising steps. Inspired by this paradigm, we propo…
Driving Behavior Explanation with Multi-level Fusion
Hédi Ben-Younes, Éloi Zablocki, Patrick Pérez +1
In this era of active development of autonomous vehicles, it becomes crucial to provide driving systems with the capacity to explain their decisions. In this work, we focus on gene…