5 code implementations • 25 Sep 2017 • Sen Wang, Ronald Clark, Hongkai Wen, Niki Trigoni
This paper presents a novel end-to-end framework for monocular VO by using deep Recurrent Convolutional Neural Networks (RCNNs).
2 code implementations • 1 Feb 2018 • Bo Yang, Stefano Rosa, Andrew Markham, Niki Trigoni, Hongkai Wen
Unlike existing work which typically requires multiple views of the same object or class labels to recover the full 3D geometry, the proposed 3D-RecGAN++ only takes the voxel grid representation of a depth view of the object as input, and is able to generate the complete 3D occupancy grid with a high resolution of 256^3 by recovering the occluded/missing regions.
2 code implementations • 26 Aug 2017 • Bo Yang, Hongkai Wen, Sen Wang, Ronald Clark, Andrew Markham, Niki Trigoni
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 networks.
2 code implementations • ECCV 2020 • Royson Lee, Łukasz Dudziak, Mohamed Abdelfattah, Stylianos I. Venieris, Hyeji Kim, Hongkai Wen, Nicholas D. Lane
Recent works in single-image perceptual super-resolution (SR) have demonstrated unprecedented performance in generating realistic textures by means of deep convolutional networks.
1 code implementation • 13 Oct 2022 • Thomas Chun Pong Chau, Łukasz Dudziak, Hongkai Wen, Nicholas Donald Lane, Mohamed S Abdelfattah
To provide a systematic study of the performance of NAS algorithms on a macro search space, we release Blox - a benchmark that consists of 91k unique models trained on the CIFAR-100 dataset.
1 code implementation • 11 Nov 2022 • Man Luo, Bowen Du, Wenzhe Zhang, Tianyou Song, Kun Li, HongMing Zhu, Mark Birkin, Hongkai Wen
This is particularly challenging in the context of expanding systems, because i) the range of the EVs is limited while charging time is typically long, which constrain the viable rebalancing operations; and ii) the EV stations in the system are dynamically changing, i. e., the legitimate targets for rebalancing operations can vary over time.
1 code implementation • 10 Dec 2019 • Chris Xiaoxuan Lu, Bowen Du, Hongkai Wen, Sen Wang, Andrew Markham, Ivan Martinovic, Yiran Shen, Niki Trigoni
Demand for smartwatches has taken off in recent years with new models which can run independently from smartphones and provide more useful features, becoming first-class mobile platforms.
1 code implementation • 18 May 2022 • Teddy Cunningham, Konstantin Klemmer, Hongkai Wen, Hakan Ferhatosmanoglu
We introduce GeoPointGAN, a novel GAN-based solution for generating synthetic spatial point datasets with high utility and strong individual level privacy guarantees.
1 code implementation • 14 Aug 2019 • Chris Xiaoxuan Lu, Xuan Kan, Bowen Du, Changhao Chen, Hongkai Wen, Andrew Markham, Niki Trigoni, John Stankovic
Inspired by the fact that most people carry smart wireless devices with them, e. g. smartphones, we propose to use this wireless identifier as a supervisory label.
no code implementations • CVPR 2017 • Ronald Clark, Sen Wang, Andrew Markham, Niki Trigoni, Hongkai Wen
Machine learning techniques, namely convolutional neural networks (CNN) and regression forests, have recently shown great promise in performing 6-DoF localization of monocular images.
no code implementations • 29 Jan 2017 • Ronald Clark, Sen Wang, Hongkai Wen, Andrew Markham, Niki Trigoni
In this paper we present an on-manifold sequence-to-sequence learning approach to motion estimation using visual and inertial sensors.
no code implementations • 10 Mar 2019 • Man Luo, Hongkai Wen, Yi Luo, Bowen Du, Konstantin Klemmer, Hong-Ming Zhu
Electric Vehicle (EV) sharing systems have recently experienced unprecedented growth across the globe.
no code implementations • 1 Mar 2020 • Liang Du, Jingang Tan, xiangyang xue, Lili Chen, Hongkai Wen, Jianfeng Feng, Jiamao Li, Xiaolin Zhang
We propose a novel fast and robust 3D point clouds segmentation framework via coupled feature selection, named 3DCFS, that jointly performs semantic and instance segmentation.
no code implementations • 12 Jun 2021 • Lichuan Xiang, Łukasz Dudziak, Mohamed S. Abdelfattah, Thomas Chau, Nicholas D. Lane, Hongkai Wen
From this perspective, we introduce a novel \textit{perturbation-based zero-cost operation scoring} (Zero-Cost-PT) approach, which utilizes zero-cost proxies that were recently studied in multi-trial NAS but degrade significantly on larger search spaces, typical for differentiable NAS.
no code implementations • 18 Aug 2021 • Lichuan Xiang, Royson Lee, Mohamed S. Abdelfattah, Nicholas D. Lane, Hongkai Wen
Deep learning-based blind super-resolution (SR) methods have recently achieved unprecedented performance in upscaling frames with unknown degradation.
no code implementations • 3 Nov 2021 • Man Luo, Bowen Du, Konstantin Klemmer, HongMing Zhu, Hongkai Wen
Shared e-mobility services have been widely tested and piloted in cities across the globe, and already woven into the fabric of modern urban planning.
no code implementations • 6 Sep 2022 • Guangrong Zhao, Yiran Shen, Ning Chen, Pengfei Hu, Lei Liu, Hongkai Wen
By designing a series of signal processing algorithms bespoke for dynamic vision sensing on mobile devices, EV-Tach is able to extract the rotational speed accurately from the event stream produced by dynamic vision sensing on rotary targets.
no code implementations • 1 Feb 2023 • Savvas Papaioannou, Hongkai Wen, Andrew Markham, Niki Trigoni
In this paper, we propose a novel positioning system, RAVEL (Radio And Vision Enhanced Localization), which fuses anonymous visual detections captured by widely available camera infrastructure, with radio readings (e. g. WiFi radio data).
no code implementations • 30 Nov 2023 • Hrushikesh Loya, Łukasz Dudziak, Abhinav Mehrotra, Royson Lee, Javier Fernandez-Marques, Nicholas D. Lane, Hongkai Wen
Neural architecture search has proven to be a powerful approach to designing and refining neural networks, often boosting their performance and efficiency over manually-designed variations, but comes with computational overhead.