6 citations · 12 across the 3 of their papers we have counts for
4 papers
KDFNet: Learning Keypoint Distance Field for 6D Object Pose Estimation
Xingyu Liu, Shun Iwase, Kris M. Kitani
We present KDFNet, a novel method for 6D object pose estimation from RGB images. To handle occlusion, many recent works have proposed to localize 2D keypoints through pixel-wise vo…
RePOSE: Fast 6D Object Pose Refinement via Deep Texture Rendering
Shun Iwase, Xingyu Liu, Rawal Khirodkar +2
We present RePOSE, a fast iterative refinement method for 6D object pose estimation. Prior methods perform refinement by feeding zoomed-in input and rendered RGB images into a CNN…
Kinematics-Guided Reinforcement Learning for Object-Aware 3D Ego-Pose Estimation
Zhengyi Luo, Ryo Hachiuma, Ye Yuan +2
We propose a method for incorporating object interaction and human body dynamics into the task of 3D ego-pose estimation using a head-mounted camera. We use a kinematics model of t…
Epipolar-Guided Deep Object Matching for Scene Change Detection
Kento Doi, Ryuhei Hamaguchi, Shun Iwase +3
This paper describes a viewpoint-robust object-based change detection network (OBJ-CDNet). Mobile cameras such as drive recorders capture images from different viewpoints each time…