5 papers · 1 filter
HuLiGen: Human LiDAR Generation from Parametric Body Models
Salma Galaaoui, Nermin Samet, David Picard
LiDAR point clouds of humans are extremely expensive to collect and annotate, thus represent a scarce resource that hinders the development of human analysis using this modality. T…
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.…
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…
3D Human Pose and Shape Estimation from LiDAR Point Clouds: A Review
Salma Galaaoui, Eduardo Valle, David Picard +1
In this paper, we present a comprehensive review of 3D human pose estimation and human mesh recovery from in-the-wild LiDAR point clouds. We compare existing approaches across seve…
PAFUSE: Part-based Diffusion for 3D Whole-Body Pose Estimation
Nermin Samet, Cédric Rommel, David Picard +1
We introduce a novel approach for 3D whole-body pose estimation, addressing the challenge of scale -- and deformability -- variance across body parts brought by the challenge of ex…