b'Chris Russell'

research

∙ 07/20/2023

Kick Back Relax: Learning to Reconstruct the World by Watching SlowTV

Self-supervised monocular depth estimation (SS-MDE) has the potential to...

0 Jaime Spencer, et al. ∙

research

∙ 07/18/2023

Learning Adaptive Neighborhoods for Graph Neural Networks

Graph convolutional networks (GCNs) enable end-to-end learning on graph ...

0 Avishkar Saha, et al. ∙

research

∙ 04/20/2023

A data augmentation perspective on diffusion models and retrieval

Diffusion models excel at generating photorealistic images from text-que...

0 Max F. Burg, et al. ∙

research

∙ 04/14/2023

The Second Monocular Depth Estimation Challenge

This paper discusses the results for the second edition of the Monocular...

0 Jaime Spencer, et al. ∙

research

∙ 03/28/2023

Novel View Synthesis of Humans using Differentiable Rendering

We present a new approach for synthesizing novel views of people in new ...

0 Guillaume Rochette, et al. ∙

research

∙ 02/26/2023

Efficient fair PCA for fair representation learning

We revisit the problem of fair principal component analysis (PCA), where...

0 Matthäus Kleindessner, et al. ∙

research

∙ 02/05/2023

The Unfairness of Fair Machine Learning: Levelling down and strict egalitarianism by default

In recent years fairness in machine learning (ML) has emerged as a highl...

0 Brent Mittelstadt, et al. ∙

research

∙ 01/12/2023

Causal Triplet: An Open Challenge for Intervention-centric Causal Representation Learning

Recent years have seen a surge of interest in learning high-level causal...

7 Yuejiang Liu, et al. ∙

research

∙ 11/22/2022

The Monocular Depth Estimation Challenge

This paper summarizes the results of the first Monocular Depth Estimatio...

0 Jaime Spencer, et al. ∙

research

∙ 08/02/2022

Deconstructing Self-Supervised Monocular Reconstruction: The Design Decisions that Matter

This paper presents an open and comprehensive framework to systematicall...

3 Jaime Spencer, et al. ∙

research

∙ 07/19/2022

Assaying Out-Of-Distribution Generalization in Transfer Learning

Since out-of-distribution generalization is a generally ill-posed proble...

6 Florian Wenzel, et al. ∙

research

∙ 07/08/2022

Pixel-level Correspondence for Self-Supervised Learning from Video

While self-supervised learning has enabled effective representation lear...

1 Yash Sharma, et al. ∙

research

∙ 04/09/2022

Are Two Heads the Same as One? Identifying Disparate Treatment in Fair Neural Networks

We show that deep neural networks that satisfy demographic parity do so ...

0 Michael Lohaus, et al. ∙

research

∙ 04/06/2022

"The Pedestrian next to the Lamppost" Adaptive Object Graphs for Better Instantaneous Mapping

Estimating a semantically segmented bird's-eye-view (BEV) map from a sin...

0 Avishkar Saha, et al. ∙

research

∙ 03/09/2022

Leveling Down in Computer Vision: Pareto Inefficiencies in Fair Deep Classifiers

Algorithmic fairness is frequently motivated in terms of a trade-off in ...

3 Dominik Zietlow, et al. ∙

research

∙ 11/24/2021

Human Pose Manipulation and Novel View Synthesis using Differentiable Rendering

We present a new approach for synthesizing novel views of people in new ...

0 Guillaume Rochette, et al. ∙

research

∙ 10/03/2021

Translating Images into Maps

We approach instantaneous mapping, converting images to a top-down view ...

0 Avishkar Saha, et al. ∙

research

∙ 07/17/2021

Visual Representation Learning Does Not Generalize Strongly Within the Same Domain

An important component for generalization in machine learning is to unco...

14 Lukas Schott, et al. ∙

research

∙ 05/07/2021

Pairwise Fairness for Ordinal Regression

We initiate the study of fairness for ordinal regression, or ordinal cla...

0 Matthäus Kleindessner, et al. ∙

research

∙ 11/10/2020

What Did You Think Would Happen? Explaining Agent Behaviour Through Intended Outcomes

We present a novel form of explanation for Reinforcement Learning, based...

0 Herman Yau, et al. ∙

research

∙ 05/12/2020

Why Fairness Cannot Be Automated: Bridging the Gap Between EU Non-Discrimination Law and AI

This article identifies a critical incompatibility between European noti...

3 Sandra Wachter, et al. ∙

research

∙ 01/21/2020

Adequate and fair explanations

Explaining sophisticated machine-learning based systems is an important ...

11 Nicholas Asher, et al. ∙

research

∙ 12/19/2019

Adversarial Perturbations on the Perceptual Ball

We present a simple regularisation of Adversarial Perturbations based up...

0 Andrew Elliott, et al. ∙

research

∙ 09/13/2019

Weakly-Supervised 3D Pose Estimation from a Single Image using Multi-View Consistency

We present a novel data-driven regularizer for weakly-supervised learnin...

0 Guillaume Rochette, et al. ∙

research

∙ 07/23/2019

U4D: Unsupervised 4D Dynamic Scene Understanding

We introduce the first approach to solve the challenging problem of unsu...

5 Armin Mustafa, et al. ∙

research

∙ 01/02/2019

Efficient Search for Diverse Coherent Explanations

This paper proposes new search algorithms for counterfactual explanation...

0 Chris Russell, et al. ∙

research

∙ 11/04/2018

Explaining Explanations in AI

Recent work on interpretability in machine learning and AI has focused o...

0 Brent Mittelstadt, et al. ∙

research

∙ 08/04/2018

Rethinking Pose in 3D: Multi-stage Refinement and Recovery for Markerless Motion Capture

We propose a CNN-based approach for multi-camera markerless motion captu...

0 Denis Tome, et al. ∙

research

∙ 07/18/2018

Take a Look Around: Using Street View and Satellite Images to Estimate House Prices

When an individual purchases a home, they simultaneously purchase its st...

0 Stephen Law, et al. ∙

research

∙ 06/06/2018

Causal Interventions for Fairness

Most approaches in algorithmic fairness constrain machine learning metho...

0 Matt J. Kusner, et al. ∙

research

∙ 05/15/2018

Causal Reasoning for Algorithmic Fairness

In this work, we argue for the importance of causal reasoning in creatin...

0 Joshua R. Loftus, et al. ∙

research

∙ 01/10/2018

Worst-case Optimal Submodular Extensions for Marginal Estimation

Submodular extensions of an energy function can be used to efficiently c...

0 Pankaj Pansari, et al. ∙

research

∙ 11/01/2017

Counterfactual Explanations without Opening the Black Box: Automated Decisions and the GDPR

There has been much discussion of the right to explanation in the EU Gen...

0 Sandra Wachter, et al. ∙

research

∙ 08/04/2017

Better Together: Joint Reasoning for Non-rigid 3D Reconstruction with Specularities and Shading

We demonstrate the use of shape-from-shading (SfS) to improve both the q...

0 Qi Liu-Yin, et al. ∙

research

∙ 05/22/2017

VEEGAN: Reducing Mode Collapse in GANs using Implicit Variational Learning

Deep generative models provide powerful tools for distributions over com...

0 Akash Srivastava, et al. ∙

research

∙ 03/20/2017

Counterfactual Fairness

Machine learning can impact people with legal or ethical consequences wh...

0 Matt J. Kusner, et al. ∙

research

∙ 01/01/2017

Lifting from the Deep: Convolutional 3D Pose Estimation from a Single Image

We propose a unified formulation for the problem of 3D human pose estima...

0 Denis Tome, et al. ∙

research

∙ 11/13/2015

Solving Jigsaw Puzzles with Linear Programming

We propose a novel Linear Program (LP) based formula- tion for solving j...

0 Chris Russell, et al. ∙

research

∙ 09/09/2014

F-formation Detection: Individuating Free-standing Conversational Groups in Images

Detection of groups of interacting people is a very interesting and usef...

0 Francesco Setti, et al. ∙

research

∙ 03/15/2012

Exact and Approximate Inference in Associative Hierarchical Networks using Graph Cuts

Markov Networks are widely used through out computer vision and machine ...

0 Chris Russell, et al. ∙

research

∙ 09/11/2011

Efficient Minimization of Higher Order Submodular Functions using Monotonic Boolean Functions

Submodular function minimization is a key problem in a wide variety of a...

0 Srikumar Ramalingam, et al. ∙

Chris Russell

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