The University of Sydney

∙ Sydney , Australia ∙ 0 followers

We make lives better by producing leaders of society and equipping our people with leadership qualities so they can serve our communities at every level.

AdderNet: Do We Really Need Multiplications in Deep Learning?

Compared with cheap addition operation, multiplication operation is of m...
12/31/2019 ∙ by Hanting Chen, et al. ∙ 31 ∙ share

read it
Robust Visual Tracking Revisited: From Correlation Filter to Template Matching

In this paper, we propose a novel matching based tracker by investigatin...
04/15/2019 ∙ by Fanghui Liu, et al. ∙ 26 ∙ share

read it
A Unified End-to-End Framework for Efficient Deep Image Compression

Image compression is a widely used technique to reduce the spatial redun...
02/09/2020 ∙ by Jiaheng Liu, et al. ∙ 25 ∙ share

read it
A Regularization Approach for Instance-Based Superset Label Learning

Different from the traditional supervised learning in which each trainin...
04/05/2019 ∙ by Chen gong, et al. ∙ 24 ∙ share

read it
GhostNet: More Features from Cheap Operations

Deploying convolutional neural networks (CNNs) on embedded devices is di...
11/27/2019 ∙ by Kai Han, et al. ∙ 23 ∙ share

read it
A Shape Transformation-based Dataset Augmentation Framework for Pedestrian Detection

Deep learning-based computer vision is usually data-hungry. Many researc...
12/15/2019 ∙ by Zhe Chen, et al. ∙ 23 ∙ share

read it
Stacked Semantic-Guided Network for Zero-Shot Sketch-Based Image Retrieval

Zero-shot sketch-based image retrieval (ZS-SBIR) is a task of cross-doma...
04/03/2019 ∙ by Hao Wang, et al. ∙ 22 ∙ share

read it
All you need is a good representation: A multi-level and classifier-centric representation for few-shot learning

The main problems of few-shot learning are how to learn a generalized re...
11/28/2019 ∙ by Shaoli Huang, et al. ∙ 22 ∙ share

read it
Gated-GAN: Adversarial Gated Networks for Multi-Collection Style Transfer

Style transfer describes the rendering of an image semantic content as d...
04/04/2019 ∙ by Xinyuan Chen, et al. ∙ 20 ∙ share

read it
Shakeout: A New Approach to Regularized Deep Neural Network Training

Recent years have witnessed the success of deep neural networks in deali...
04/13/2019 ∙ by Guoliang Kang, et al. ∙ 20 ∙ share

read it
Progressive Retinex: Mutually Reinforced Illumination-Noise Perception Network for Low Light Image Enhancement

Contrast enhancement and noise removal are coupled problems for low-ligh...
11/26/2019 ∙ by Yang Wang, et al. ∙ 20 ∙ share

read it
An Underwater Image Enhancement Benchmark Dataset and Beyond

Underwater image enhancement has been attracting much attention due to i...
01/11/2019 ∙ by Chongyi Li, et al. ∙ 18 ∙ share

read it
Deep Learning Based Unsupervised and Semi-supervised Classification for Keratoconus

The transparent cornea is the window of the eye, facilitating the entry ...
01/31/2020 ∙ by Nicole Hallett, et al. ∙ 18 ∙ share

read it
GradNet: Gradient-Guided Network for Visual Object Tracking

The fully-convolutional siamese network based on template matching has s...
09/15/2019 ∙ by Peixia Li, et al. ∙ 17 ∙ share

read it
Local Deep-Feature Alignment for Unsupervised Dimension Reduction

This paper presents an unsupervised deep-learning framework named Local ...
04/22/2019 ∙ by Jian Zhang, et al. ∙ 16 ∙ share

read it
Transferring Knowledge Fragments for Learning Distance Metric from A Heterogeneous Domain

The goal of transfer learning is to improve the performance of target le...
04/08/2019 ∙ by Yong Luo, et al. ∙ 14 ∙ share

read it
Semi-supervised Learning Approach to Generate Neuroimaging Modalities with Adversarial Training

Magnetic Resonance Imaging (MRI) of the brain can come in the form of di...
12/09/2019 ∙ by Harrison Nguyen, et al. ∙ 14 ∙ share

read it
Transfer Metric Learning: Algorithms, Applications and Outlooks

Distance metric learning (DML) aims to find an appropriate way to reveal...
10/09/2018 ∙ by Yong Luo, et al. ∙ 12 ∙ share

read it
Fast Efficient Object Detection Using Selective Attention

Deep learning object detectors achieve state-of-the-art accuracy at the ...
11/19/2018 ∙ by Shivanthan Yohanandan, et al. ∙ 12 ∙ share

read it
EcoNAS: Finding Proxies for Economical Neural Architecture Search

Neural Architecture Search (NAS) achieves significant progress in many c...
01/05/2020 ∙ by Dongzhan Zhou, et al. ∙ 11 ∙ share

read it
Fully-Featured Attribute Transfer

Image attribute transfer aims to change an input image to a target one w...
02/17/2019 ∙ by De Xie, et al. ∙ 10 ∙ share

read it
Data-Free Learning of Student Networks

Learning portable neural networks is very essential for computer vision ...
04/02/2019 ∙ by Hanting Chen, et al. ∙ 10 ∙ share

read it
Active Transfer Learning Network: A Unified Deep Joint Spectral-Spatial Feature Learning Model For Hyperspectral Image Classification

Deep learning has recently attracted significant attention in the field ...
04/04/2019 ∙ by Cheng Deng, et al. ∙ 10 ∙ share

read it
Robust and Discriminative Labeling for Multi-label Active Learning Based on Maximum Correntropy Criterion

Multi-label learning draws great interests in many real world applicatio...
04/14/2019 ∙ by Bo Du, et al. ∙ 10 ∙ share

read it
RNAS: Architecture Ranking for Powerful Networks

Neural Architecture Search (NAS) is attractive for automatically produci...
09/30/2019 ∙ by Yixing Xu, et al. ∙ 10 ∙ share

read it
Towards High Performance Human Keypoint Detection

Human keypoint detection from a single image is very challenging due to ...
02/03/2020 ∙ by Jing Zhang, et al. ∙ 10 ∙ share

read it
Multimodal Unified Attention Networks for Vision-and-Language Interactions

Learning an effective attention mechanism for multimodal data is importa...
08/12/2019 ∙ by Zhou Yu, et al. ∙ 9 ∙ share

read it
Epileptic Seizure Classification with Symmetric and Hybrid Bilinear Models

Epilepsy affects nearly 1 be treated by anti-epileptic drugs and a much ...
01/15/2020 ∙ by Tennison Liu, et al. ∙ 9 ∙ share

read it
Computer vision-based framework for extracting geological lineaments from optical remote sensing data

The extraction of geological lineaments from digital satellite data is a...
10/04/2018 ∙ by Ehsan Farahbakhsh, et al. ∙ 8 ∙ share

read it
Learning Student Networks via Feature Embedding

Deep convolutional neural networks have been widely used in numerous app...
12/17/2018 ∙ by Hanting Chen, et al. ∙ 8 ∙ share

read it
Adapting Stochastic Block Models to Power-Law Degree Distributions

Stochastic block models (SBMs) have been playing an important role in mo...
04/05/2019 ∙ by Maoying Qiao, et al. ∙ 8 ∙ share

read it
Segmentation-Aware Image Denoising without Knowing True Segmentation

Several recent works discussed application-driven image restoration neur...
05/22/2019 ∙ by Sicheng Wang, et al. ∙ 8 ∙ share

read it
AM-LFS: AutoML for Loss Function Search

Designing an effective loss function plays an important role in visual a...
05/17/2019 ∙ by Chuming Li, et al. ∙ 7 ∙ share

read it
Positive-Unlabeled Compression on the Cloud

Many attempts have been done to extend the great success of convolutiona...
09/21/2019 ∙ by Yixing Xu, et al. ∙ 7 ∙ share

read it
Where-and-When to Look: Deep Siamese Attention Networks for Video-based Person Re-identification

Video-based person re-identification (re-id) is a central application in...
08/03/2018 ∙ by Lin Wu, et al. ∙ 6 ∙ share

read it
Sparse-to-Continuous: Enhancing Monocular Depth Estimation using Occupancy Maps

This paper addresses the problem of single image depth estimation (SIDE)...
09/24/2018 ∙ by Nícolas Rosa, et al. ∙ 6 ∙ share

read it
Orthogonal Deep Neural Networks

In this paper, we introduce the algorithms of Orthogonal Deep Neural Net...
05/15/2019 ∙ by Kui Jia, et al. ∙ 6 ∙ share

read it
Online Hyper-parameter Learning for Auto-Augmentation Strategy

Data augmentation is critical to the success of modern deep learning tec...
05/17/2019 ∙ by Chen Lin, et al. ∙ 6 ∙ share

read it
On Positive-Unlabeled Classification in GAN

This paper defines a positive and unlabeled classification problem for s...
02/04/2020 ∙ by Tianyu Guo, et al. ∙ 6 ∙ share

read it
Bringing Giant Neural Networks Down to Earth with Unlabeled Data

Compressing giant neural networks has gained much attention for their ex...
07/13/2019 ∙ by Yehui Tang, et al. ∙ 5 ∙ share

read it
Learning Instance-wise Sparsity for Accelerating Deep Models

Exploring deep convolutional neural networks of high efficiency and low ...
07/27/2019 ∙ by Chuanjian Liu, et al. ∙ 5 ∙ share

read it
Balanced Binary Neural Networks with Gated Residual

Binary neural networks have attracted numerous attention in recent years...
09/26/2019 ∙ by Mingzhu Shen, et al. ∙ 5 ∙ share

read it
BayesLands: A Bayesian inference approach for parameter uncertainty quantification in Badlands

Bayesian inference provides a principled approach towards uncertainty qu...
05/02/2018 ∙ by Rohitash Chandra, et al. ∙ 4 ∙ share

read it
Cost-Sensitive Feature Selection by Optimizing F-Measures

Feature selection is beneficial for improving the performance of general...
04/04/2019 ∙ by Meng Liu, et al. ∙ 4 ∙ share

read it
Grapy-ML: Graph Pyramid Mutual Learning for Cross-dataset Human Parsing

Human parsing, or human body part semantic segmentation, has been an act...
11/27/2019 ∙ by Haoyu He, et al. ∙ 4 ∙ share

read it
Confidence Scores Make Instance-dependent Label-noise Learning Possible

Learning with noisy labels has drawn a lot of attention. In this area, m...
01/11/2020 ∙ by Antonin Berthon, et al. ∙ 4 ∙ share

read it
Contextualized Spatial-Temporal Network for Taxi Origin-Destination Demand Prediction

Taxi demand prediction has recently attracted increasing research intere...
05/15/2019 ∙ by Lingbo Liu, et al. ∙ 3 ∙ share

read it
FAMED-Net: A Fast and Accurate Multi-scale End-to-end Dehazing Network

Single image dehazing is a critical image pre-processing step for subseq...
06/11/2019 ∙ by Jing Zhang, et al. ∙ 3 ∙ share

read it
Attribute Aware Pooling for Pedestrian Attribute Recognition

This paper expands the strength of deep convolutional neural networks (C...
07/27/2019 ∙ by Kai Han, et al. ∙ 3 ∙ share

read it
PAD-Net: Multi-Tasks Guided Prediction-and-Distillation Network for Simultaneous Depth Estimation and Scene Parsing

Depth estimation and scene parsing are two particularly important tasks ...
05/11/2018 ∙ by Dan Xu, et al. ∙ 2 ∙ share

read it

The University of Sydney

Featured Researchers