189 citations · 314 across the 11 of their papers we have counts for
11 papers
Local-to-Global Panorama Inpainting for Locale-Aware Indoor Lighting Prediction
Jiayang Bai, Zhen He, Shan Yang +4
Predicting panoramic indoor lighting from a single perspective image is a fundamental but highly ill-posed problem in computer vision and graphics. To achieve locale-aware and robu…
A systematic review of the use of Deep Learning in Satellite Imagery for Agriculture
Brandon Victor, Zhen He, Aiden Nibali
Agricultural research is essential for increasing food production to meet the requirements of an increasing population in the coming decades. Recently, satellite technology has bee…
Spatial Transformer Network with Transfer Learning for Small-scale Fine-grained Skeleton-based Tai Chi Action Recognition
Lin Yuan, Zhen He, Qiang Wang +2
Human action recognition is a quite hugely investigated area where most remarkable action recognition networks usually use large-scale coarse-grained action datasets of daily human…
Deep Graph Learning for Spatially-Varying Indoor Lighting Prediction
Jiayang Bai, Jie Guo, Chenchen Wan +6
Lighting prediction from a single image is becoming increasingly important in many vision and augmented reality (AR) applications in which shading and shadow consistency between vi…
Semi-supervised learning for medical image classification using imbalanced training data
Tri Huynh, Aiden Nibali, Zhen He
Medical image classification is often challenging for two reasons: a lack of labelled examples due to expensive and time-consuming annotation protocols, and imbalanced class labels…
Pose is all you need: The pose only group activity recognition system (POGARS)
Haritha Thilakarathne, Aiden Nibali, Zhen He +1
We introduce a novel deep learning based group activity recognition approach called the Pose Only Group Activity Recognition System (POGARS), designed to use only tracked poses of…
Enhancing Trajectory Prediction using Sparse Outputs: Application to Team Sports
Brandon Victor, Aiden Nibali, Zhen He +1
Sophisticated trajectory prediction models that effectively mimic team dynamics have many potential uses for sports coaches, broadcasters and spectators. However, through experimen…
Tracking by Animation: Unsupervised Learning of Multi-Object Attentive Trackers
Zhen He, Jian Li, Daxue Liu +2
Online Multi-Object Tracking (MOT) from videos is a challenging computer vision task which has been extensively studied for decades. Most of the existing MOT algorithms are based o…
3D Human Pose Estimation with 2D Marginal Heatmaps
Aiden Nibali, Zhen He, Stuart Morgan +1
Automatically determining three-dimensional human pose from monocular RGB image data is a challenging problem. The two-dimensional nature of the input results in intrinsic ambiguit…
Numerical Coordinate Regression with Convolutional Neural Networks
Aiden Nibali, Zhen He, Stuart Morgan +1
We study deep learning approaches to inferring numerical coordinates for points of interest in an input image. Existing convolutional neural network-based solutions to this problem…
Wider and Deeper, Cheaper and Faster: Tensorized LSTMs for Sequence Learning
Zhen He, Shaobing Gao, Liang Xiao +3
Long Short-Term Memory (LSTM) is a popular approach to boosting the ability of Recurrent Neural Networks to store longer term temporal information. The capacity of an LSTM network…