546 citations · 1.3k across the 25 of their papers we have counts for
6 papers · 1 filter
Kick Back & Relax: Learning to Reconstruct the World by Watching SlowTV
Jaime Spencer, Chris Russell, Simon Hadfield +1
Self-supervised monocular depth estimation (SS-MDE) has the potential to scale to vast quantities of data. Unfortunately, existing approaches limit themselves to the automotive dom…
Learning Adaptive Neighborhoods for Graph Neural Networks
Avishkar Saha, Oscar Mendez, Chris Russell +1
Graph convolutional networks (GCNs) enable end-to-end learning on graph structured data. However, many works assume a given graph structure. When the input graph is noisy or unavai…
The Second Monocular Depth Estimation Challenge
Jaime Spencer, C. Stella Qian, Michaela Trescakova +40
This paper discusses the results for the second edition of the Monocular Depth Estimation Challenge (MDEC). This edition was open to methods using any form of supervision, includin…
Image retrieval outperforms diffusion models on data augmentation
Max F. Burg, Florian Wenzel, Dominik Zietlow +4
Many approaches have been proposed to use diffusion models to augment training datasets for downstream tasks, such as classification. However, diffusion models are themselves train…
Novel View Synthesis of Humans using Differentiable Rendering
Guillaume Rochette, Chris Russell, Richard Bowden
We present a new approach for synthesizing novel views of people in new poses. Our novel differentiable renderer enables the synthesis of highly realistic images from any viewpoint…
Efficient fair PCA for fair representation learning
Matthäus Kleindessner, Michele Donini, Chris Russell +1
We revisit the problem of fair principal component analysis (PCA), where the goal is to learn the best low-rank linear approximation of the data that obfuscates demographic informa…