34 citations · 104 across the 13 of their papers we have counts for
4 papers · 2 filters
Unsupervised Domain Adaptation with Temporal-Consistent Self-Training for 3D Hand-Object Joint Reconstruction
Mengshi Qi, Edoardo Remelli, Mathieu Salzmann +1
Deep learning-solutions for hand-object 3D pose and shape estimation are now very effective when an annotated dataset is available to train them to handle the scenarios and lightin…
UCLID-Net: Single View Reconstruction in Object Space
Benoit Guillard, Edoardo Remelli, Pascal Fua
Most state-of-the-art deep geometric learning single-view reconstruction approaches rely on encoder-decoder architectures that output either shape parametrizations or implicit repr…
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…
Lightweight Multi-View 3D Pose Estimation through Camera-Disentangled Representation
Edoardo Remelli, Shangchen Han, Sina Honari +2
We present a lightweight solution to recover 3D pose from multi-view images captured with spatially calibrated cameras. Building upon recent advances in interpretable representatio…