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Jonathan Tremblay
NVIDIA
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Computer Vision
Robotics
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FACTORSIM: Generative Simulation via Factorized Representation
NeRFDeformer: NeRF Transformation from a Single View via 3D Scene Flows
Neural Implicit Representation for Building Digital Twins of Unknown Articulated Objects
Partial-View Object View Synthesis via Filtering Inversion
HANDAL: A Dataset of Real-World Manipulable Object Categories with Pose Annotations, Affordances, and Reconstructions
BundleSDF: Neural 6-DoF Tracking and 3D Reconstruction of Unknown Objects
One-Shot Neural Fields for 3D Object Understanding
TTA-COPE: Test-Time Adaptation for Category-Level Object Pose Estimation
Parallel Inversion of Neural Radiance Fields for Robust Pose Estimation
PROGPROMPT: Generating Situated Robot Task Plans using Large Language Models
RGB-Only Reconstruction of Tabletop Scenes for Collision-Free Manipulator Control
MegaPose: 6D Pose Estimation of Novel Objects via Render and Compare
6-DoF Pose Estimation of Household Objects for Robotic Manipulation: An Accessible Dataset and Benchmark
RTMV: A Ray-Traced Multi-View Synthetic Dataset for Novel View Synthesis
Efficient Geometry-aware 3D Generative Adversarial Networks
Watch It Move: Unsupervised Discovery of 3D Joints for Re-Posing of Articulated Objects
Keypoint-Based Category-Level Object Pose Tracking from an RGB Sequence with Uncertainty Estimation
Single-Stage Keypoint-Based Category-Level Object Pose Estimation from an RGB Image
Joint Space Control via Deep Reinforcement Learning
Multi-View Fusion for Multi-Level Robotic Scene Understanding
DexYCB: A Benchmark for Capturing Hand Grasping of Objects
Fast Uncertainty Quantification for Deep Object Pose Estimation
Hierarchical Planning for Long-Horizon Manipulation with Geometric and Symbolic Scene Graphs
NViSII: A Scriptable Tool for Photorealistic Image Generation
Indirect Object-to-Robot Pose Estimation from an External Monocular RGB Camera
Camera-to-robot pose estimation from a single image
Toward Sim-to-Real Directional Semantic Grasping
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