Search Results for author: Derek Nowrouzezahrai

Found 33 papers, 19 papers with code

Efficient Graphics Representation with Differentiable Indirection

no code implementations12 Sep 2023 Sayantan Datta, Carl Marshall, Derek Nowrouzezahrai, Zhao Dong, Zhengqin Li

We introduce differentiable indirection -- a novel learned primitive that employs differentiable multi-scale lookup tables as an effective substitute for traditional compute and data operations across the graphics pipeline.

A Model-Based Solution to the Offline Multi-Agent Reinforcement Learning Coordination Problem

no code implementations26 May 2023 Paul Barde, Jakob Foerster, Derek Nowrouzezahrai, Amy Zhang

Training multiple agents to coordinate is an important problem with applications in robotics, game theory, economics, and social sciences.

Multi-agent Reinforcement Learning

MeshDiffusion: Score-based Generative 3D Mesh Modeling

1 code implementation14 Mar 2023 Zhen Liu, Yao Feng, Michael J. Black, Derek Nowrouzezahrai, Liam Paull, Weiyang Liu

We consider the task of generating realistic 3D shapes, which is useful for a variety of applications such as automatic scene generation and physical simulation.

Scene Generation

Attention-based Neural Cellular Automata

no code implementations2 Nov 2022 Mattie Tesfaldet, Derek Nowrouzezahrai, Christopher Pal

We introduce an instance of this class named $\textit{Vision Transformer Cellular Automata}$ (ViTCA).


Learning Neural Implicit Representations with Surface Signal Parameterizations

1 code implementation1 Nov 2022 Yanran Guan, Andrei Chubarau, Ruby Rao, Derek Nowrouzezahrai

Traditional explicit object representations commonly couple the 3D shape data with auxiliary surface-mapped image data, such as diffuse color textures and fine-scale geometric details in normal maps that typically require a mapping of the 3D surface onto a plane, i. e., a surface parameterization; implicit representations, on the other hand, cannot be easily textured due to lack of configurable surface parameterization.

Learning Latent Structural Causal Models

no code implementations24 Oct 2022 Jithendaraa Subramanian, Yashas Annadani, Ivaxi Sheth, Nan Rosemary Ke, Tristan Deleu, Stefan Bauer, Derek Nowrouzezahrai, Samira Ebrahimi Kahou

For linear Gaussian additive noise SCMs, we present a tractable approximate inference method which performs joint inference over the causal variables, structure and parameters of the latent SCM from random, known interventions.

Bayesian Inference Image Generation +1

Uncertainty-Driven Active Vision for Implicit Scene Reconstruction

1 code implementation3 Oct 2022 Edward J. Smith, Michal Drozdzal, Derek Nowrouzezahrai, David Meger, Adriana Romero-Soriano

We evaluate our proposed approach on the ABC dataset and the in the wild CO3D dataset, and show that: (1) we are able to obtain high quality state-of-the-art occupancy reconstructions; (2) our perspective conditioned uncertainty definition is effective to drive improvements in next best view selection and outperforms strong baseline approaches; and (3) we can further improve shape understanding by performing a gradient-based search on the view selection candidates.

Scene Understanding

Overcoming challenges in leveraging GANs for few-shot data augmentation

1 code implementation30 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 +1

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

2 code implementations 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.

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.

reinforcement-learning Reinforcement Learning (RL)

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

3 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 +1

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 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.

Open-Ended Question Answering reinforcement-learning +1

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

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.

Navigate Reinforcement Learning (RL)

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 Inductive Bias +3

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 +3

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