337 citations · 419 across the 17 of their papers we have counts for
4 papers · 1 filter
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…
Training with Quantization Noise for Extreme Model Compression
Angela Fan, Pierre Stock, Benjamin Graham +4
We tackle the problem of producing compact models, maximizing their accuracy for a given model size. A standard solution is to train networks with Quantization Aware Training, wher…