Search Results for author: Derek Nowrouzezahrai

Found 24 papers, 14 papers with code

Overcoming challenges in leveraging GANs for few-shot data augmentation

no code implementations30 Mar 2022 Christopher Beckham, Issam Laradji, Pau Rodriguez, David Vazquez, Derek Nowrouzezahrai, Christopher Pal

In this paper, we explore the use of GAN-based few-shot data augmentation as a method to improve few-shot classification performance.

Classification Data Augmentation

Learning to Guide and to Be Guided in the Architect-Builder Problem

1 code implementation ICLR 2022 Paul Barde, Tristan Karch, Derek Nowrouzezahrai, Clément Moulin-Frier, Christopher Pal, Pierre-Yves Oudeyer

ABIG results in a low-level, high-frequency, guiding communication protocol that not only enables an architect-builder pair to solve the task at hand, but that can also generalize to unseen tasks.

Imitation Learning

SSR: Semi-supervised Soft Rasterizer for single-view 2D to 3D Reconstruction

1 code implementation21 Aug 2021 Issam Laradji, Pau Rodríguez, David Vazquez, Derek Nowrouzezahrai

In order to obtain the viewpoints for these unlabeled images, we propose to use a Siamese network that takes two images as input and outputs whether they correspond to the same viewpoint.

3D Reconstruction

Robust Motion In-betweening

1 code implementation9 Feb 2021 Félix G. Harvey, Mike Yurick, Derek Nowrouzezahrai, Christopher Pal

To quantitatively evaluate performance on transitions and generalizations to longer time horizons, we present well-defined in-betweening benchmarks on a subset of the widely used Human3. 6M dataset and on LaFAN1, a novel high quality motion capture dataset that is more appropriate for transition generation.

Human Pose Forecasting motion prediction +1

Neural Geometric Level of Detail: Real-time Rendering with Implicit 3D Shapes

1 code implementation CVPR 2021 Towaki Takikawa, Joey Litalien, Kangxue Yin, Karsten Kreis, Charles Loop, Derek Nowrouzezahrai, Alec Jacobson, Morgan McGuire, Sanja Fidler

We introduce an efficient neural representation that, for the first time, enables real-time rendering of high-fidelity neural SDFs, while achieving state-of-the-art geometry reconstruction quality.

Visual Question Answering From Another Perspective: CLEVR Mental Rotation Tests

no code implementations1 Jan 2021 Christopher Beckham, Martin Weiss, Florian Golemo, Sina Honari, Derek Nowrouzezahrai, Christopher Pal

To do this we have created a new version of the CLEVR VQA problem setup and dataset that we call CLEVR Mental Rotation Tests or CLEVR-MRT, where the goal is to answer questions about the original CLEVR viewpoint given a single image obtained from a different viewpoint of the same scene.

3D Reconstruction Contrastive Learning +4

Affinity LCFCN: Learning to Segment Fish with Weak Supervision

1 code implementation6 Nov 2020 Issam Laradji, Alzayat Saleh, Pau Rodriguez, Derek Nowrouzezahrai, Mostafa Rahimi Azghadi, David Vazquez

Leading automatic approaches rely on fully-supervised segmentation models to acquire these measurements but these require collecting per-pixel labels -- also time consuming and laborious: i. e., it can take up to two minutes per fish to generate accurate segmentation labels, almost always requiring at least some manual intervention.

Regularized Inverse Reinforcement Learning

no code implementations ICLR 2021 Wonseok Jeon, Chen-Yang Su, Paul Barde, Thang Doan, Derek Nowrouzezahrai, Joelle Pineau

Inverse Reinforcement Learning (IRL) aims to facilitate a learner's ability to imitate expert behavior by acquiring reward functions that explain the expert's decisions.


On the Effectiveness of Weight-Encoded Neural Implicit 3D Shapes

3 code implementations17 Sep 2020 Thomas Davies, Derek Nowrouzezahrai, Alec Jacobson

Many prior works have focused on _latent-encoded_ neural implicits, where a latent vector encoding of a specific shape is also fed as input.

3D Shape Representation

A Weakly Supervised Consistency-based Learning Method for COVID-19 Segmentation in CT Images

4 code implementations4 Jul 2020 Issam Laradji, Pau Rodriguez, Oscar Mañas, Keegan Lensink, Marco Law, Lironne Kurzman, William Parker, David Vazquez, Derek Nowrouzezahrai

Thus, we propose a consistency-based (CB) loss function that encourages the output predictions to be consistent with spatial transformations of the input images.

Adversarial Soft Advantage Fitting: Imitation Learning without Policy Optimization

3 code implementations NeurIPS 2020 Paul Barde, Julien Roy, Wonseok Jeon, Joelle Pineau, Christopher Pal, Derek Nowrouzezahrai

Adversarial Imitation Learning alternates between learning a discriminator -- which tells apart expert's demonstrations from generated ones -- and a generator's policy to produce trajectories that can fool this discriminator.

Imitation Learning reinforcement-learning

Surprisal-Triggered Conditional Computation with Neural Networks

1 code implementation2 Jun 2020 Loren Lugosch, Derek Nowrouzezahrai, Brett H. Meyer

The surprisal of the input, measured as the negative log-likelihood of the current observation according to the autoregressive model, is used as a measure of input difficulty.

Speech Recognition

Pix2Shape: Towards Unsupervised Learning of 3D Scenes from Images using a View-based Representation

1 code implementation23 Mar 2020 Sai Rajeswar, Fahim Mannan, Florian Golemo, Jérôme Parent-Lévesque, David Vazquez, Derek Nowrouzezahrai, Aaron Courville

We propose Pix2Shape, an approach to solve this problem with four components: (i) an encoder that infers the latent 3D representation from an image, (ii) a decoder that generates an explicit 2. 5D surfel-based reconstruction of a scene from the latent code (iii) a differentiable renderer that synthesizes a 2D image from the surfel representation, and (iv) a critic network trained to discriminate between images generated by the decoder-renderer and those from a training distribution.

Scalable Multi-Agent Inverse Reinforcement Learning via Actor-Attention-Critic

no code implementations24 Feb 2020 Wonseok Jeon, Paul Barde, Derek Nowrouzezahrai, Joelle Pineau

Multi-agent adversarial inverse reinforcement learning (MA-AIRL) is a recent approach that applies single-agent AIRL to multi-agent problems where we seek to recover both policies for our agents and reward functions that promote expert-like behavior.


Robo-PlaNet: Learning to Poke in a Day

no code implementations9 Nov 2019 Maxime Chevalier-Boisvert, Guillaume Alain, Florian Golemo, Derek Nowrouzezahrai

Recently, the Deep Planning Network (PlaNet) approach was introduced as a model-based reinforcement learning method that learns environment dynamics directly from pixel observations.

Model-based Reinforcement Learning reinforcement-learning

Navigation Agents for the Visually Impaired: A Sidewalk Simulator and Experiments

1 code implementation29 Oct 2019 Martin Weiss, Simon Chamorro, Roger Girgis, Margaux Luck, Samira E. Kahou, Joseph P. Cohen, Derek Nowrouzezahrai, Doina Precup, Florian Golemo, Chris Pal

In our endeavor to create a navigation assistant for the BVI, we found that existing Reinforcement Learning (RL) environments were unsuitable for the task.

Using Speech Synthesis to Train End-to-End Spoken Language Understanding Models

2 code implementations21 Oct 2019 Loren Lugosch, Brett Meyer, Derek Nowrouzezahrai, Mirco Ravanelli

End-to-end models are an attractive new approach to spoken language understanding (SLU) in which the meaning of an utterance is inferred directly from the raw audio without employing the standard pipeline composed of a separately trained speech recognizer and natural language understanding module.

Data Augmentation Natural Language Understanding +2

Promoting Coordination through Policy Regularization in Multi-Agent Deep Reinforcement Learning

no code implementations NeurIPS 2020 Julien Roy, Paul Barde, Félix G. Harvey, Derek Nowrouzezahrai, Christopher Pal

Finally, we analyze the effects of our proposed methods on the policies that our agents learn and show that our methods successfully enforce the qualities that we propose as proxies for coordinated behaviors.

Continuous Control Multi-agent Reinforcement Learning +1

Pix2Scene: Learning Implicit 3D Representations from Images

no code implementations ICLR 2019 Sai Rajeswar, Fahim Mannan, Florian Golemo, David Vazquez, Derek Nowrouzezahrai, Aaron Courville

Modelling 3D scenes from 2D images is a long-standing problem in computer vision with implications in, e. g., simulation and robotics.

Hyperparameter Optimization in Black-box Image Processing using Differentiable Proxies

1 code implementation SIGGRAPH 2019 2019 Ethan Tseng, Felix Yu, Yuting Yang, Fahim Mannan, Karl St. Arnaud, Derek Nowrouzezahrai, Jean-François Lalonde, Felix Heide

We present a fully automatic system to optimize the parameters of black-box hardware and software image processing pipelines according to any arbitrary (i. e., application-specific) metric.

Hyperparameter Optimization Image Denoising +2

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