337 citations · 416 across the 9 of their papers we have counts for
12 papers · 1 filter
Self-Supervised Correspondence Estimation via Multiview Registration
Mohamed El Banani, Ignacio Rocco, David Novotny +4
Video provides us with the spatio-temporal consistency needed for visual learning. Recent approaches have utilized this signal to learn correspondence estimation from close-by fram…
DensePose 3D: Lifting Canonical Surface Maps of Articulated Objects to the Third Dimension
Roman Shapovalov, David Novotny, Benjamin Graham +2
We tackle the problem of monocular 3D reconstruction of articulated objects like humans and animals. We contribute DensePose 3D, a method that can learn such reconstructions in a w…
LeViT: a Vision Transformer in ConvNet's Clothing for Faster Inference
Ben Graham, Alaaeldin El-Nouby, Hugo Touvron +4
We design a family of image classification architectures that optimize the trade-off between accuracy and efficiency in a high-speed regime. Our work exploits recent findings in at…
Exploring Data-Efficient 3D Scene Understanding with Contrastive Scene Contexts
Ji Hou, Benjamin Graham, Matthias Nießner +1
The rapid progress in 3D scene understanding has come with growing demand for data; however, collecting and annotating 3D scenes (e.g. point clouds) are notoriously hard. For examp…
RidgeSfM: Structure from Motion via Robust Pairwise Matching Under Depth Uncertainty
Benjamin Graham, David Novotny
We consider the problem of simultaneously estimating a dense depth map and camera pose for a large set of images of an indoor scene. While classical SfM pipelines rely on a two-ste…
3D Multi-bodies: Fitting Sets of Plausible 3D Human Models to Ambiguous Image Data
Benjamin Biggs, Sébastien Ehrhadt, Hanbyul Joo +3
We consider the problem of obtaining dense 3D reconstructions of humans from single and partially occluded views. In such cases, the visual evidence is usually insufficient to iden…