Jonathan Tremblay

research

∙ 08/02/2023

HANDAL: A Dataset of Real-World Manipulable Object Categories with Pose Annotations, Affordances, and Reconstructions

We present the HANDAL dataset for category-level object pose estimation ...

0 Andrew Guo, et al. ∙

research

∙ 03/29/2023

TTA-COPE: Test-Time Adaptation for Category-Level Object Pose Estimation

Test-time adaptation methods have been gaining attention recently as a p...

0 Taeyeop Lee, et al. ∙

research

∙ 03/24/2023

BundleSDF: Neural 6-DoF Tracking and 3D Reconstruction of Unknown Objects

We present a near real-time method for 6-DoF tracking of an unknown obje...

3 Bowen Wen, et al. ∙

research

∙ 12/13/2022

MegaPose: 6D Pose Estimation of Novel Objects via Render Compare

We introduce MegaPose, a method to estimate the 6D pose of novel objects...

0 Yann Labbé, et al. ∙

research

∙ 10/21/2022

Neural Fields for Robotic Object Manipulation from a Single Image

We present a unified and compact representation for object rendering, 3D...

0 Valts Blukis, et al. ∙

research

∙ 10/18/2022

Parallel Inversion of Neural Radiance Fields for Robust Pose Estimation

We present a parallelized optimization method based on fast Neural Radia...

2 Yunzhi Lin, et al. ∙

research

∙ 09/22/2022

ProgPrompt: Generating Situated Robot Task Plans using Large Language Models

Task planning can require defining myriad domain knowledge about the wor...

1 Ishika Singh, et al. ∙

research

∙ 06/15/2022

Variable Bitrate Neural Fields

Neural approximations of scalar and vector fields, such as signed distan...

15 Towaki Takikawa, et al. ∙

research

∙ 05/23/2022

Keypoint-Based Category-Level Object Pose Tracking from an RGB Sequence with Uncertainty Estimation

We propose a single-stage, category-level 6-DoF pose estimation algorith...

0 Yunzhi Lin, et al. ∙

research

∙ 05/14/2022

RTMV: A Ray-Traced Multi-View Synthetic Dataset for Novel View Synthesis

We present a large-scale synthetic dataset for novel view synthesis cons...

13 Jonathan Tremblay, et al. ∙

research

∙ 03/11/2022

6-DoF Pose Estimation of Household Objects for Robotic Manipulation: An Accessible Dataset and Benchmark

We present a new dataset for 6-DoF pose estimation of known objects, wit...

20 Stephen Tyree, et al. ∙

research

∙ 12/21/2021

Watch It Move: Unsupervised Discovery of 3D Joints for Re-Posing of Articulated Objects

Rendering articulated objects while controlling their poses is critical ...

10 Atsuhiro Noguchi, et al. ∙

research

∙ 12/15/2021

Efficient Geometry-aware 3D Generative Adversarial Networks

Unsupervised generation of high-quality multi-view-consistent images and...

9 Eric R. Chan, et al. ∙

research

∙ 09/13/2021

Single-stage Keypoint-based Category-level Object Pose Estimation from an RGB Image

Prior work on 6-DoF object pose estimation has largely focused on instan...

0 Yunzhi Lin, et al. ∙

research

∙ 05/28/2021

NViSII: A Scriptable Tool for Photorealistic Image Generation

We present a Python-based renderer built on NVIDIA's OptiX ray tracing e...

9 Nathan Morrical, et al. ∙

research

∙ 04/09/2021

DexYCB: A Benchmark for Capturing Hand Grasping of Objects

We introduce DexYCB, a new dataset for capturing hand grasping of object...

5 Yu-Wei Chao, et al. ∙

research

∙ 03/25/2021

Multi-view Fusion for Multi-level Robotic Scene Understanding

We present a system for multi-level scene awareness for robotic manipula...

0 Yunzhi Lin, et al. ∙

research

∙ 12/14/2020

Hierarchical Planning for Long-Horizon Manipulation with Geometric and Symbolic Scene Graphs

We present a visually grounded hierarchical planning algorithm for long-...

0 Yifeng Zhu, et al. ∙

research

∙ 11/16/2020

Fast Uncertainty Quantification for Deep Object Pose Estimation

Deep learning-based object pose estimators are often unreliable and over...

0 Guanya Shi, et al. ∙

research

∙ 11/12/2020

Joint Space Control via Deep Reinforcement Learning

The dominant way to control a robot manipulator uses hand-crafted differ...

0 Visak Kumar, et al. ∙

research

∙ 08/26/2020

Indirect Object-to-Robot Pose Estimation from an External Monocular RGB Camera

We present a robotic grasping system that uses a single external monocul...

0 Jonathan Tremblay, et al. ∙

research

∙ 05/21/2020

Guided Uncertainty-Aware Policy Optimization: Combining Learning and Model-Based Strategies for Sample-Efficient Policy Learning

Traditional robotic approaches rely on an accurate model of the environm...

33 Michelle A. Lee, et al. ∙

research

∙ 05/02/2020

PAMTRI: Pose-Aware Multi-Task Learning for Vehicle Re-Identification Using Highly Randomized Synthetic Data

In comparison with person re-identification (ReID), which has been widel...

1 Zheng Tang, et al. ∙

research

∙ 11/21/2019

Contextual Reinforcement Learning of Visuo-tactile Multi-fingered Grasping Policies

Using simulation to train robot manipulation policies holds the promise ...

0 Visak Kumar, et al. ∙

research

∙ 11/21/2019

Camera-to-Robot Pose Estimation from a Single Image

We present an approach for estimating the pose of a camera with respect ...

0 Timothy E. Lee, et al. ∙

research

∙ 09/04/2019

Directional Semantic Grasping of Real-World Objects: From Simulation to Reality

We present a deep reinforcement learning approach to grasp semantically ...

0 Shariq Iqbal, et al. ∙

research

∙ 05/13/2019

Few-Shot Viewpoint Estimation

Viewpoint estimation for known categories of objects has been improved s...

4 Hung-Yu Tseng, et al. ∙

research

∙ 09/27/2018

Deep Object Pose Estimation for Semantic Robotic Grasping of Household Objects

Using synthetic data for training deep neural networks for robotic manip...

0 Jonathan Tremblay, et al. ∙

research

∙ 05/18/2018

Synthetically Trained Neural Networks for Learning Human-Readable Plans from Real-World Demonstrations

We present a system to infer and execute a human-readable program from a...

0 Jonathan Tremblay, et al. ∙

research

∙ 04/18/2018

Falling Things: A Synthetic Dataset for 3D Object Detection and Pose Estimation

We present a new dataset, called Falling Things (FAT), for advancing the...

0 Jonathan Tremblay, et al. ∙

research

∙ 04/18/2018

Training Deep Networks with Synthetic Data: Bridging the Reality Gap by Domain Randomization

We present a system for training deep neural networks for object detecti...

0 Jonathan Tremblay, et al. ∙

Jonathan Tremblay

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