962 citations · 2.1k across the 31 of their papers we have counts for
6 papers · 1 filter
DeepVO: Towards End-to-End Visual Odometry with Deep Recurrent Convolutional Neural Networks
Sen Wang, Ronald Clark, Hongkai Wen +1
This paper studies monocular visual odometry (VO) problem. Most of existing VO algorithms are developed under a standard pipeline including feature extraction, feature matching, mo…
3D Object Reconstruction from a Single Depth View with Adversarial Learning
Bo Yang, Hongkai Wen, Sen Wang +3
In this paper, we propose a novel 3D-RecGAN approach, which reconstructs the complete 3D structure of a given object from a single arbitrary depth view using generative adversarial…
Towards Monocular Vision based Obstacle Avoidance through Deep Reinforcement Learning
Linhai Xie, Sen Wang, Andrew Markham +1
Obstacle avoidance is a fundamental requirement for autonomous robots which operate in, and interact with, the real world. When perception is limited to monocular vision avoiding c…
VidLoc: A Deep Spatio-Temporal Model for 6-DoF Video-Clip Relocalization
Ronald Clark, Sen Wang, Andrew Markham +2
Machine learning techniques, namely convolutional neural networks (CNN) and regression forests, have recently shown great promise in performing 6-DoF localization of monocular imag…
Detailed Surface Geometry and Albedo Recovery from RGB-D Video Under Natural Illumination
Xinxin Zuo, Sen Wang, Jiangbin Zheng +1
In this paper we present a novel approach for depth map enhancement from an RGB-D video sequence. The basic idea is to exploit the shading information in the color image. Instead o…
VINet: Visual-Inertial Odometry as a Sequence-to-Sequence Learning Problem
Ronald Clark, Sen Wang, Hongkai Wen +2
In this paper we present an on-manifold sequence-to-sequence learning approach to motion estimation using visual and inertial sensors. It is to the best of our knowledge the first…