7 citations · 19 across the 7 of their papers we have counts for
5 papers · 1 filter
Instance-specific 6-DoF Object Pose Estimation from Minimal Annotations
Rohan Pratap Singh, Iori Kumagai, Antonio Gabas +3
In many robotic applications, the environment setting in which the 6-DoF pose estimation of a known, rigid object and its subsequent grasping is to be performed, remains nearly unc…
Object Memory Transformer for Object Goal Navigation
Rui Fukushima, Kei Ota, Asako Kanezaki +2
This paper presents a reinforcement learning method for object goal navigation (ObjNav) where an agent navigates in 3D indoor environments to reach a target object based on long-te…
Rapid Pose Label Generation through Sparse Representation of Unknown Objects
Rohan Pratap Singh, Mehdi Benallegue, Yusuke Yoshiyasu +1
Deep Convolutional Neural Networks (CNNs) have been successfully deployed on robots for 6-DoF object pose estimation through visual perception. However, obtaining labeled data on a…
Learning Body Shape and Pose from Dense Correspondences
Yusuke Yoshiyasu, Lucas Gamez
In this paper, we address the problem of learning 3D human pose and body shape from 2D image dataset, without having to use 3D dataset (body shape and pose). The idea is to use den…
Skeleton Transformer Networks: 3D Human Pose and Skinned Mesh from Single RGB Image
Yusuke Yoshiyasu, Ryusuke Sagawa, Ko Ayusawa +1
In this paper, we present Skeleton Transformer Networks (SkeletonNet), an end-to-end framework that can predict not only 3D joint positions but also 3D angular pose (bone rotations…