activity
20162022
most citedBacktracking Regression Forests for Accurate Camera Relocalization

14 citations · 24 across the 3 of their papers we have counts for

collaborators

12 papers

cs.CV202210 cited

DigiFace-1M: 1 Million Digital Face Images for Face Recognition

Gwangbin Bae, Martin de La Gorce, Tadas Baltrusaitis +5

State-of-the-art face recognition models show impressive accuracy, achieving over 99.8% on Labeled Faces in the Wild (LFW) dataset. Such models are trained on large-scale datasets…

cs.CV2021

FastNeRF: High-Fidelity Neural Rendering at 200FPS

Stephan J. Garbin, Marek Kowalski, Matthew Johnson +2

Recent work on Neural Radiance Fields (NeRF) showed how neural networks can be used to encode complex 3D environments that can be rendered photorealistically from novel viewpoints.…

cs.GR2020

LSMAT Least Squares Medial Axis Transform

Daniel Rebain, Baptiste Angles, Julien Valentin +4

The medial axis transform has applications in numerous fields including visualization, computer graphics, and computer vision. Unfortunately, traditional medial axis transformation…

cs.CV2019

ViewAL: Active Learning with Viewpoint Entropy for Semantic Segmentation

Yawar Siddiqui, Julien Valentin, Matthias Nießner

We propose ViewAL, a novel active learning strategy for semantic segmentation that exploits viewpoint consistency in multi-view datasets. Our core idea is that inconsistencies in m…

cs.CV2019

Multiview Aggregation for Learning Category-Specific Shape Reconstruction

Srinath Sridhar, Davis Rempe, Julien Valentin +2

We investigate the problem of learning category-specific 3D shape reconstruction from a variable number of RGB views of previously unobserved object instances. Most approaches for…

cs.CV2019

Normalized Object Coordinate Space for Category-Level 6D Object Pose and Size Estimation

He Wang, Srinath Sridhar, Jingwei Huang +3

The goal of this paper is to estimate the 6D pose and dimensions of unseen object instances in an RGB-D image. Contrary to "instance-level" 6D pose estimation tasks, our problem as…