The University of Sydney

research

∙ 02/23/2020

Beyond Dropout: Feature Map Distortion to Regularize Deep Neural Networks

Deep neural networks often consist of a great number of trainable parame...

Yehui Tang, et al. ∙

research

∙ 03/23/2020

Distillating Knowledge from Graph Convolutional Networks

Existing knowledge distillation methods focus on convolutional neural ne...

Yiding Yang, et al. ∙

research

∙ 07/24/2022

Online Continual Learning with Contrastive Vision Transformer

Online continual learning (online CL) studies the problem of learning se...

Zhen Wang, et al. ∙

research

∙ 03/15/2021

Learning Frequency-aware Dynamic Network for Efficient Super-Resolution

Deep learning based methods, especially convolutional neural networks (C...

Wenbin Xie, et al. ∙

research

∙ 04/28/2020

Deep Conversational Recommender Systems: A New Frontier for Goal-Oriented Dialogue Systems

In recent years, the emerging topics of recommender systems that take ad...

Dai Hoang Tran, et al. ∙

research

∙ 06/13/2022

Better Teacher Better Student: Dynamic Prior Knowledge for Knowledge Distillation

Knowledge distillation (KD) has shown very promising capabilities in tra...

Zengyu Qiu, et al. ∙

research

∙ 01/25/2021

AdderNet and its Minimalist Hardware Design for Energy-Efficient Artificial Intelligence

Convolutional neural networks (CNN) have been widely used for boosting t...

Yunhe Wang, et al. ∙

research

∙ 12/31/2019

AdderNet: Do We Really Need Multiplications in Deep Learning?

Compared with cheap addition operation, multiplication operation is of m...

Hanting Chen, et al. ∙

research

∙ 04/15/2019

Robust Visual Tracking Revisited: From Correlation Filter to Template Matching

In this paper, we propose a novel matching based tracker by investigatin...

Fanghui Liu, et al. ∙

research

∙ 02/09/2020

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

Image compression is a widely used technique to reduce the spatial redun...

Jiaheng Liu, et al. ∙

research

∙ 04/05/2019

A Regularization Approach for Instance-Based Superset Label Learning

Different from the traditional supervised learning in which each trainin...

Chen gong, et al. ∙

research

∙ 11/27/2019

GhostNet: More Features from Cheap Operations

Deploying convolutional neural networks (CNNs) on embedded devices is di...

Kai Han, et al. ∙

research

∙ 12/15/2019

A Shape Transformation-based Dataset Augmentation Framework for Pedestrian Detection

Deep learning-based computer vision is usually data-hungry. Many researc...

Zhe Chen, et al. ∙

research

∙ 07/16/2021

Self-Supervised Learning Framework for Remote Heart Rate Estimation Using Spatiotemporal Augmentation

Recent supervised deep learning methods have shown that heart rate can b...

Hao Wang, et al. ∙

research

∙ 04/03/2019

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...

Hao Wang, et al. ∙

research

∙ 11/28/2019

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...

Shaoli Huang, et al. ∙

research

∙ 08/18/2021

SynFace: Face Recognition with Synthetic Data

With the recent success of deep neural networks, remarkable progress has...

Haibo Qiu, et al. ∙

research

∙ 04/04/2019

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

Style transfer describes the rendering of an image semantic content as d...

Xinyuan Chen, et al. ∙

research

∙ 04/13/2019

Shakeout: A New Approach to Regularized Deep Neural Network Training

Recent years have witnessed the success of deep neural networks in deali...

Guoliang Kang, et al. ∙

research

∙ 11/26/2019

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

Contrast enhancement and noise removal are coupled problems for low-ligh...

Yang Wang, et al. ∙

research

∙ 02/20/2020

Multi-Agent Meta-Reinforcement Learning for Self-Powered and Sustainable Edge Computing Systems

The stringent requirements of mobile edge computing (MEC) applications a...

Md. Shirajum Munir, et al. ∙

research

∙ 05/05/2020

Unsupervised Instance Segmentation in Microscopy Images via Panoptic Domain Adaptation and Task Re-weighting

Unsupervised domain adaptation (UDA) for nuclei instance segmentation is...

Dongnan Liu, et al. ∙

research

∙ 05/07/2020

A Review of Computer Vision Methods in Network Security

Network security has become an area of significant importance more than ...

Jiawei Zhao, et al. ∙

research

∙ 06/14/2022

TransVG++: End-to-End Visual Grounding with Language Conditioned Vision Transformer

In this work, we explore neat yet effective Transformer-based frameworks...

Jiajun Deng, et al. ∙

research

∙ 01/11/2019

An Underwater Image Enhancement Benchmark Dataset and Beyond

Underwater image enhancement has been attracting much attention due to i...

Chongyi Li, et al. ∙

research

∙ 01/31/2020

Deep Learning Based Unsupervised and Semi-supervised Classification for Keratoconus

The transparent cornea is the window of the eye, facilitating the entry ...

Nicole Hallett, et al. ∙

research

∙ 02/07/2022

3D Object Detection from Images for Autonomous Driving: A Survey

3D object detection from images, one of the fundamental and challenging ...

Xinzhu Ma, et al. ∙

research

∙ 09/15/2019

GradNet: Gradient-Guided Network for Visual Object Tracking

The fully-convolutional siamese network based on template matching has s...

Peixia Li, et al. ∙

research

∙ 04/25/2020

Deep Multimodal Neural Architecture Search

Designing effective neural networks is fundamentally important in deep m...

Zhou Yu, et al. ∙

research

∙ 02/10/2022

On Real-time Image Reconstruction with Neural Networks for MRI-guided Radiotherapy

MRI-guidance techniques that dynamically adapt radiation beams to follow...

David E. J. Waddington, et al. ∙

research

∙ 04/20/2022

Multi-Component Optimization and Efficient Deployment of Neural-Networks on Resource-Constrained IoT Hardware

The majority of IoT devices like smartwatches, smart plugs, HVAC control...

Bharath Sudharsan, et al. ∙

research

∙ 04/22/2019

Local Deep-Feature Alignment for Unsupervised Dimension Reduction

This paper presents an unsupervised deep-learning framework named Local ...

Jian Zhang, et al. ∙

research

∙ 02/22/2020

Deep Learning for Ultra-Reliable and Low-Latency Communications in 6G Networks

In the future 6th generation networks, ultra-reliable and low-latency co...

Changyang She, et al. ∙

research

∙ 04/04/2022

Unsupervised Learning of Accurate Siamese Tracking

Unsupervised learning has been popular in various computer vision tasks,...

Qiuhong Shen, et al. ∙

research

∙ 01/03/2021

Dynamics, behaviours, and anomaly persistence in cryptocurrencies and equities surrounding COVID-19

This paper uses new and recently introduced methodologies to study the s...

Nick James, et al. ∙

research

∙ 09/30/2021

Unsupervised Landmark Detection Based Spatiotemporal Motion Estimation for 4D Dynamic Medical Images

Motion estimation is a fundamental step in dynamic medical image process...

Yuyu Guo, et al. ∙

research

∙ 04/08/2019

Transferring Knowledge Fragments for Learning Distance Metric from A Heterogeneous Domain

The goal of transfer learning is to improve the performance of target le...

Yong Luo, et al. ∙

research

∙ 12/09/2019

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...

Harrison Nguyen, et al. ∙

research

∙ 02/05/2022

Unsupervised Learning on 3D Point Clouds by Clustering and Contrasting

Learning from unlabeled or partially labeled data to alleviate human lab...

Guofeng Mei, et al. ∙

research

∙ 10/09/2018

Transfer Metric Learning: Algorithms, Applications and Outlooks

Distance metric learning (DML) aims to find an appropriate way to reveal...

Yong Luo, et al. ∙

research

∙ 03/07/2020

Distilling portable Generative Adversarial Networks for Image Translation

Despite Generative Adversarial Networks (GANs) have been widely used in ...

Hanting Chen, et al. ∙

research

∙ 05/10/2022

Domain Invariant Masked Autoencoders for Self-supervised Learning from Multi-domains

Generalizing learned representations across significantly different visu...

Haiyang Yang, et al. ∙

research

∙ 11/19/2018

Fast Efficient Object Detection Using Selective Attention

Deep learning object detectors achieve state-of-the-art accuracy at the ...

Shivanthan Yohanandan, et al. ∙

research

∙ 01/05/2020

EcoNAS: Finding Proxies for Economical Neural Architecture Search

Neural Architecture Search (NAS) achieves significant progress in many c...

Dongzhan Zhou, et al. ∙

research

∙ 02/17/2020

Discernible Compressed Images via Deep Perception Consistency

Image compression, as one of the fundamental low-level image processing ...

Zhaohui Yang, et al. ∙

research

∙ 04/17/2020

Conservative Plane Releasing for Spatial Privacy Protection in Mixed Reality

Augmented reality (AR) or mixed reality (MR) platforms require spatial u...

Jaybie A. de Guzman, et al. ∙

research

∙ 05/29/2020

HourNAS: Extremely Fast Neural Architecture Search Through an Hourglass Lens

Neural Architecture Search (NAS) refers to automatically design the arch...

Zhaohui Yang, et al. ∙

research

∙ 11/27/2020

Temporal-Channel Transformer for 3D Lidar-Based Video Object Detection in Autonomous Driving

The strong demand of autonomous driving in the industry has lead to stro...

Zhenxun Yuan, et al. ∙

research

∙ 12/09/2021

A Bayesian Treatment of Real-to-Sim for Deformable Object Manipulation

Deformable object manipulation remains a challenging task in robotics re...

Rika Antonova, et al. ∙

research

∙ 03/10/2022

Contrastive Boundary Learning for Point Cloud Segmentation

Point cloud segmentation is fundamental in understanding 3D environments...

Liyao Tang, et al. ∙

The University of Sydney

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