2 citations · 6 across the 10 of their papers we have counts for
10 papers
Estimating Velocity and Spin of Spherical Objects from Rolling-Shutter Image(s)
Wenjie Xue, Jun Yang, Jingmin Wang +1
Rolling-shutter cameras introduce characteristic distortions when imaging fast moving objects, and these effects are typically treated as artifacts to be corrected. In this work, w…
Active 6D Pose Estimation for Textureless Objects using Multi-View RGB Frames
Jun Yang, Wenjie Xue, Sahar Ghavidel +1
Estimating the 6D pose of textureless objects from RGB images is an important problem in robotics. Due to appearance ambiguities, rotational symmetries, and severe occlusions, sing…
Uncertainty-aware 3D Object-Level Mapping with Deep Shape Priors
Ziwei Liao, Jun Yang, Jingxing Qian +2
3D object-level mapping is a fundamental problem in robotics, which is especially challenging when object CAD models are unavailable during inference. In this work, we propose a fr…
Active Pose Refinement for Textureless Shiny Objects using the Structured Light Camera
Jun Yang, Jian Yao, Steven L. Waslander
6D pose estimation of textureless shiny objects has become an essential problem in many robotic applications. Many pose estimators require high-quality depth data, often measured b…
Pixel Difference Convolutional Network for RGB-D Semantic Segmentation
Jun Yang, Lizhi Bai, Yaoru Sun +3
RGB-D semantic segmentation can be advanced with convolutional neural networks due to the availability of Depth data. Although objects cannot be easily discriminated by just the 2D…
6D Pose Estimation for Textureless Objects on RGB Frames using Multi-View Optimization
Jun Yang, Wenjie Xue, Sahar Ghavidel +1
6D pose estimation of textureless objects is a valuable but challenging task for many robotic applications. In this work, we propose a framework to address this challenge using onl…
POCD: Probabilistic Object-Level Change Detection and Volumetric Mapping in Semi-Static Scenes
Jingxing Qian, Veronica Chatrath, Jun Yang +3
Maintaining an up-to-date map to reflect recent changes in the scene is very important, particularly in situations involving repeated traversals by a robot operating in an environm…
Next-Best-View Prediction for Active Stereo Cameras and Highly Reflective Objects
Jun Yang, Steven L. Waslander
Depth acquisition with the active stereo camera is a challenging task for highly reflective objects. When setup permits, multi-view fusion can provide increased levels of depth com…
ROBI: A Multi-View Dataset for Reflective Objects in Robotic Bin-Picking
Jun Yang, Yizhou Gao, Dong Li +1
In robotic bin-picking applications, the perception of texture-less, highly reflective parts is a valuable but challenging task. The high glossiness can introduce fake edges in RGB…
Probabilistic Multi-View Fusion of Active Stereo Depth Maps for Robotic Bin-Picking
Jun Yang, Dong Li, Steven L. Waslander
The reliable fusion of depth maps from multiple viewpoints has become an important problem in many 3D reconstruction pipelines. In this work, we investigate its impact on robotic b…