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Toyota Research Institute
Applied and forward-looking research to create a new world of mobility that's safe, reliable, accessible and pervasive.

Toyota Research Institute is sponsoring and participating at the upcoming Conference on Computer Vision and Pattern Recognition

The conference on Computer Vision and Pattern Recognition (CVPR) is one of the top international venues in Computer Science, with a focus on Computer Vision and Machine Learning. CVPR 2021 is happening virtually, June 19–25. Toyota Research Institute (TRI) is once again a top sponsor and involved in a variety of activities described below. Here are some events where TRI researchers (bolded below) will be present. We look forward to seeing you online and talking with you at this year’s CVPR!

Main Conference

Sparse Auxiliary Networks for Unified Monocular Depth Prediction and Completion

Vitor Guizilini…


Beyond self-supervised learning for depth estimation.

By: Vitor Guizilini, Rares Ambrus, Adrien Gaidon

Learning to predict depth from images, using not only geometry but also other sources of information when available.

In our previous post, we discussed how deep neural networks can predict depth from a single image. In particular, we showed that this problem can be self-supervised using only videos and geometric constraints. This approach is highly scalable and can even work on uncalibrated cameras or multi-camera rigs commonly used for autonomous driving.

However, there are some inherent limitations of self-supervised learning for monocular depth estimation, for instance, scale ambiguity. Thankfully, these issues can be addressed by adding minimal additional information. …


Self-supervised learning and beyond for depth estimation from images.

By: Vitor Guizilini, Rares Ambrus, Adrien Gaidon

Self-supervised learning enables the prediction of accurate pointclouds from a single image using only videos as training data.

Introduction

Computer Vision is a field of Artificial Intelligence that enables computers to represent the visual world. Deep Learning has revolutionized this field thanks to neural networks that can learn from data how to make accurate predictions. Recent progress promises to make cars safer, increase freedom to move through automated vehicles, and eventually provide robotic assistance for those with disabilities and for our rapidly aging global population.

However, there is a catch. Beyond privacy…


By: Russ Tedrake, V.P. Robotics Research

A rendered simulation in Drake showcasing our advanced contact modeling.

When I joined Toyota Research Institute (TRI) more than five years ago, I believed that an industrial research lab like TRI could make fundamental contributions to robotics that would be hard to make in an academic lab or a startup. And I joined with a commitment that we would share our best tools and results with the world through open-source software.


How TRI is making the future of electric mobility a reality

By: Brian Storey, Director of AMDD, Toyota Research Institute

The Accelerated Materials Design and Discovery (AMDD) group at Toyota Research Institute (TRI) is dedicated to making electrified mobility a reality. We are a group of researchers working closely with universities to help make electric vehicles (EVs) efficient, affordable, reliable, and truly emissions free. At Toyota, we think of EVs as one solution in our diverse portfolio of sustainable vehicles that includes battery electric, plug-in hybrid, and fuel cell powertrains.

Toyota Research Institute

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