262 citations · 1.1k across the 28 of their papers we have counts for
5 papers · 1 filter
Towards A Deep Insight into Landmark-based Visual Place Recognition: Methodology and Practice
Bo Yang, Jun Li, Xiaosu Xu +1
In this paper, we address the problem of landmark-based visual place recognition. In the state-of-the-art method, accurate object proposal algorithms are first leveraged for genera…
Robust Attentional Aggregation of Deep Feature Sets for Multi-view 3D Reconstruction
Bo Yang, Sen Wang, Andrew Markham +1
We study the problem of recovering an underlying 3D shape from a set of images. Existing learning based approaches usually resort to recurrent neural nets, e.g., GRU, or intuitive…
3D-PhysNet: Learning the Intuitive Physics of Non-Rigid Object Deformations
Zhihua Wang, Stefano Rosa, Bo Yang +3
The ability to interact and understand the environment is a fundamental prerequisite for a wide range of applications from robotics to augmented reality. In particular, predicting…
Defo-Net: Learning Body Deformation using Generative Adversarial Networks
Zhihua Wang, Stefano Rosa, Linhai Xie +4
Modelling the physical properties of everyday objects is a fundamental prerequisite for autonomous robots. We present a novel generative adversarial network (Defo-Net), able to pre…
Dense 3D Object Reconstruction from a Single Depth View
Bo Yang, Stefano Rosa, Andrew Markham +2
In this paper, we propose a novel approach, 3D-RecGAN++, which reconstructs the complete 3D structure of a given object from a single arbitrary depth view using generative adversar…