activity
20182026
most citedMegaPose: 6D Pose Estimation of Novel Objects via Render & Compare

70 citations · 223 across the 26 of their papers we have counts for

collaborators
Showing 2021 · cs.CVShow all

5 papers · 2 filters

cs.CV2021

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

Atsuhiro Noguchi, Umar Iqbal, Jonathan Tremblay +2

Rendering articulated objects while controlling their poses is critical to applications such as virtual reality or animation for movies. Manipulating the pose of an object, however…

cs.CV2021★ 46 cited

Efficient Geometry-aware 3D Generative Adversarial Networks

Eric R. Chan, Connor Z. Lin, Matthew A. Chan +9

Unsupervised generation of high-quality multi-view-consistent images and 3D shapes using only collections of single-view 2D photographs has been a long-standing challenge. Existing…

cs.CV2021★ 3 cited

Single-Stage Keypoint-Based Category-Level Object Pose Estimation from an RGB Image

Yunzhi Lin, Jonathan Tremblay, Stephen Tyree +2

Prior work on 6-DoF object pose estimation has largely focused on instance-level processing, in which a textured CAD model is available for each object being detected. Category-lev…

cs.CV2021★ 9 cited

NViSII: A Scriptable Tool for Photorealistic Image Generation

Nathan Morrical, Jonathan Tremblay, Yunzhi Lin +4

We present a Python-based renderer built on NVIDIA's OptiX ray tracing engine and the OptiX AI denoiser, designed to generate high-quality synthetic images for research in computer…

cs.CV2021★ 7 cited

DexYCB: A Benchmark for Capturing Hand Grasping of Objects

Yu-Wei Chao, Wei Yang, Yu Xiang +9

We introduce DexYCB, a new dataset for capturing hand grasping of objects. We first compare DexYCB with a related one through cross-dataset evaluation. We then present a thorough b…