Search Results for author: Chris Russell

Found 32 papers, 13 papers with code

Human Pose Manipulation and Novel View Synthesis using Differentiable Rendering

1 code implementation24 Nov 2021 Guillaume Rochette, Chris Russell, Richard Bowden

We show how our approach can be used for motion transfer between individuals; novel view synthesis of individuals captured from just a single camera; to synthesize individuals from any virtual viewpoint; and to re-render people in novel poses.

Image Reconstruction Novel View Synthesis

Translating Images into Maps

1 code implementation3 Oct 2021 Avishkar Saha, Oscar Mendez Maldonado, Chris Russell, Richard Bowden

We show how a novel form of transformer network can be used to map from images and video directly to an overhead map or bird's-eye-view (BEV) of the world, in a single end-to-end network.

Translation

Visual Representation Learning Does Not Generalize Strongly Within the Same Domain

1 code implementation17 Jul 2021 Lukas Schott, Julius von Kügelgen, Frederik Träuble, Peter Gehler, Chris Russell, Matthias Bethge, Bernhard Schölkopf, Francesco Locatello, Wieland Brendel

An important component for generalization in machine learning is to uncover underlying latent factors of variation as well as the mechanism through which each factor acts in the world.

Representation Learning

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

1 code implementation NeurIPS 2020 Herman Yau, Chris Russell, Simon Hadfield

We present a novel form of explanation for Reinforcement Learning, based around the notion of intended outcome.

Active Sampling for Min-Max Fairness

no code implementations11 Jun 2020 Jacob Abernethy, Pranjal Awasthi, Matthäus Kleindessner, Jamie Morgenstern, Chris Russell, Jie Zhang

We propose simple active sampling and reweighting strategies for optimizing min-max fairness that can be applied to any classification or regression model that is learned via loss minimization.

Fairness

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

1 code implementation12 May 2020 Sandra Wachter, Brent Mittelstadt, Chris Russell

Through this proposal for procedural regularity in the identification and assessment of automated discrimination, we clarify how to build considerations of fairness into automated systems as far as possible while still respecting and enabling the contextual approach to judicial interpretation practiced under EU non-discrimination law.

Fairness

Adequate and fair explanations

no code implementations21 Jan 2020 Nicholas Asher, Soumya Paul, Chris Russell

This partiality makes it possible to hide explicit biases present in the algorithm that may be injurious or unfair. We investigate how easy it is to uncover these biases in providing complete and fair explanations by exploiting the structure of the set of counterfactuals providing a complete local explanation.

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

no code implementations13 Sep 2019 Guillaume Rochette, Chris Russell, Richard Bowden

We present a novel data-driven regularizer for weakly-supervised learning of 3D human pose estimation that eliminates the drift problem that affects existing approaches.

3D Human Pose Estimation 3D Pose Estimation +1

U4D: Unsupervised 4D Dynamic Scene Understanding

no code implementations ICCV 2019 Armin Mustafa, Chris Russell, Adrian Hilton

We introduce the first approach to solve the challenging problem of unsupervised 4D visual scene understanding for complex dynamic scenes with multiple interacting people from multi-view video.

3D Pose Estimation Instance Segmentation +2

Efficient Search for Diverse Coherent Explanations

1 code implementation2 Jan 2019 Chris Russell

This paper proposes new search algorithms for counterfactual explanations based upon mixed integer programming.

Explaining Explanations in AI

no code implementations4 Nov 2018 Brent Mittelstadt, Chris Russell, Sandra Wachter

Recent work on interpretability in machine learning and AI has focused on the building of simplified models that approximate the true criteria used to make decisions.

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

no code implementations18 Jul 2018 Stephen Law, Brooks Paige, Chris Russell

Not only do few quantitative methods exist that can measure the urban environment, but that the collection of such data is both costly and subjective.

Causal Interventions for Fairness

no code implementations6 Jun 2018 Matt J. Kusner, Chris Russell, Joshua R. Loftus, Ricardo Silva

Most approaches in algorithmic fairness constrain machine learning methods so the resulting predictions satisfy one of several intuitive notions of fairness.

Fairness

Causal Reasoning for Algorithmic Fairness

no code implementations15 May 2018 Joshua R. Loftus, Chris Russell, Matt J. Kusner, Ricardo Silva

In this work, we argue for the importance of causal reasoning in creating fair algorithms for decision making.

Decision Making Fairness

Worst-case Optimal Submodular Extensions for Marginal Estimation

1 code implementation10 Jan 2018 Pankaj Pansari, Chris Russell, M. Pawan Kumar

Submodular extensions of an energy function can be used to efficiently compute approximate marginals via variational inference.

Variational Inference

When Worlds Collide: Integrating Different Counterfactual Assumptions in Fairness

no code implementations NeurIPS 2017 Chris Russell, Matt J. Kusner, Joshua Loftus, Ricardo Silva

In this paper, we show how it is possible to make predictions that are approximately fair with respect to multiple possible causal models at once, thus mitigating the problem of exact causal specification.

Counterfactual Inference Fairness

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

4 code implementations1 Nov 2017 Sandra Wachter, Brent Mittelstadt, Chris Russell

We suggest data controllers should offer a particular type of explanation, unconditional counterfactual explanations, to support these three aims.

Decision Making

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

no code implementations4 Aug 2017 Qi Liu-Yin, Rui Yu, Lourdes Agapito, Andrew Fitzgibbon, Chris Russell

We demonstrate the use of shape-from-shading (SfS) to improve both the quality and the robustness of 3D reconstruction of dynamic objects captured by a single camera.

3D Reconstruction Object Tracking

VEEGAN: Reducing Mode Collapse in GANs using Implicit Variational Learning

1 code implementation NeurIPS 2017 Akash Srivastava, Lazar Valkov, Chris Russell, Michael U. Gutmann, Charles Sutton

Deep generative models provide powerful tools for distributions over complicated manifolds, such as those of natural images.

Counterfactual Fairness

1 code implementation NeurIPS 2017 Matt J. Kusner, Joshua R. Loftus, Chris Russell, Ricardo Silva

Machine learning can impact people with legal or ethical consequences when it is used to automate decisions in areas such as insurance, lending, hiring, and predictive policing.

Causal Inference Fairness

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

10 code implementations CVPR 2017 Denis Tome, Chris Russell, Lourdes Agapito

We propose a unified formulation for the problem of 3D human pose estimation from a single raw RGB image that reasons jointly about 2D joint estimation and 3D pose reconstruction to improve both tasks.

3D Pose Estimation Monocular 3D Human Pose Estimation +1

Direct, Dense, and Deformable: Template-Based Non-Rigid 3D Reconstruction From RGB Video

no code implementations ICCV 2015 Rui Yu, Chris Russell, Neill D. F. Campbell, Lourdes Agapito

In contrast, our method makes use of a single RGB video as input; it can capture the deformations of generic shapes; and the depth estimation is dense, per-pixel and direct.

3D Reconstruction Depth Estimation +1

Solving Jigsaw Puzzles with Linear Programming

no code implementations13 Nov 2015 Rui Yu, Chris Russell, Lourdes Agapito

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

Part-Based Modelling of Compound Scenes From Images

no code implementations CVPR 2015 Anton van den Hengel, Chris Russell, Anthony Dick, John Bastian, Daniel Pooley, Lachlan Fleming, Lourdes Agapito

We propose a method to recover the structure of a compound scene from multiple silhouettes.

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

no code implementations9 Sep 2014 Francesco Setti, Chris Russell, Chiara Bassetti, Marco Cristani

Then, as a main contribution, we present a brand new method for the automatic detection of groups in still images, which is based on a graph-cuts framework for clustering individuals; in particular we are able to codify in a computational sense the sociological definition of F-formation, that is very useful to encode a group having only proxemic information: position and orientation of people.

Learning a Manifold as an Atlas

no code implementations CVPR 2013 Nikolaos Pitelis, Chris Russell, Lourdes Agapito

In this work, we return to the underlying mathematical definition of a manifold and directly characterise learning a manifold as finding an atlas, or a set of overlapping charts, that accurately describe local structure.

3D Reconstruction

Efficient Minimization of Higher Order Submodular Functions using Monotonic Boolean Functions

no code implementations11 Sep 2011 Srikumar Ramalingam, Chris Russell, Lubor Ladicky, Philip H. S. Torr

E +n^4 {\log}^{O(1)} n)$ where $E$ is the time required to evaluate the function and $n$ is the number of variables \cite{Lee2015}.

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