22 citations · 37 across the 5 of their papers we have counts for
6 papers
Score Distillation via Reparametrized DDIM
Artem Lukoianov, Haitz Sáez de Ocáriz Borde, Kristjan Greenewald +4
While 2D diffusion models generate realistic, high-detail images, 3D shape generation methods like Score Distillation Sampling (SDS) built on these 2D diffusion models produce cart…
DeepMesh: Differentiable Iso-Surface Extraction
Benoit Guillard, Edoardo Remelli, Artem Lukoianov +4
Geometric Deep Learning has recently made striking progress with the advent of continuous deep implicit fields. They allow for detailed modeling of watertight surfaces of arbitrary…
Masksembles for Uncertainty Estimation
Nikita Durasov, Timur Bagautdinov, Pierre Baque +1
Deep neural networks have amply demonstrated their prowess but estimating the reliability of their predictions remains challenging. Deep Ensembles are widely considered as being on…
MeshSDF: Differentiable Iso-Surface Extraction
Edoardo Remelli, Artem Lukoianov, Stephan R. Richter +4
Geometric Deep Learning has recently made striking progress with the advent of continuous Deep Implicit Fields. They allow for detailed modeling of watertight surfaces of arbitrary…
Social Scene Understanding: End-to-End Multi-Person Action Localization and Collective Activity Recognition
Timur Bagautdinov, Alexandre Alahi, François Fleuret +2
We present a unified framework for understanding human social behaviors in raw image sequences. Our model jointly detects multiple individuals, infers their social actions, and est…
Principled Parallel Mean-Field Inference for Discrete Random Fields
Pierre Baqué, Timur Bagautdinov, François Fleuret +1
Mean-field variational inference is one of the most popular approaches to inference in discrete random fields. Standard mean-field optimization is based on coordinate descent and i…