Chunhua Shen

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CSIRO ∙ The University of Adelaide ∙ Apple, Inc.

I am a Professor of Computer Science at University of Adelaide, leading the Statistical Machine Learning Group at School of Computer Science and Australian Institute for Machine Learning.

BlendMask: Top-Down Meets Bottom-Up for Instance Segmentation

Instance segmentation is one of the fundamental vision tasks. Recently, ...
01/02/2020 ∙ by Hao Chen, et al. ∙ 29 ∙ share

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Separating Content from Style Using Adversarial Learning for Recognizing Text in the Wild

In this work we propose to improve text recognition from a new perspecti...
01/13/2020 ∙ by Canjie Luo, et al. ∙ 27 ∙ share

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SOLO: Segmenting Objects by Locations

We present a new, embarrassingly simple approach to instance segmentatio...
12/10/2019 ∙ by Xinlong Wang, et al. ∙ 26 ∙ share

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Exploring the Capacity of Sequential-free Box Discretization Network for Omnidirectional Scene Text Detection

Omnidirectional scene text detection has received increasing research at...
12/20/2019 ∙ by Yuliang Liu, et al. ∙ 24 ∙ share

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PolarMask: Single Shot Instance Segmentation with Polar Representation

In this paper, we introduce an anchor-box free and single shot instance ...
09/29/2019 ∙ by Enze Xie, et al. ∙ 23 ∙ share

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From Open Set to Closed Set: Supervised Spatial Divide-and-Conquer for Object Counting

Visual counting, a task that aims to estimate the number of objects from...
01/07/2020 ∙ by Haipeng Xiong, et al. ∙ 20 ∙ share

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Weakly-supervised Deep Anomaly Detection with Pairwise Relation Learning

This paper studies a rarely explored but critical anomaly detection prob...
10/30/2019 ∙ by Guansong, et al. ∙ 19 ∙ share

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Deep Anomaly Detection with Deviation Networks

Although deep learning has been applied to successfully address many dat...
11/19/2019 ∙ by Guansong, et al. ∙ 17 ∙ share

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Learning and Memorizing Representative Prototypes for 3D Point Cloud Semantic and Instance Segmentation

3D point cloud semantic and instance segmentation is crucial and fundame...
01/06/2020 ∙ by Tong He, et al. ∙ 17 ∙ share

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Attention-guided Network for Ghost-free High Dynamic Range Imaging

Ghosting artifacts caused by moving objects or misalignments is a key ch...
04/23/2019 ∙ by Qingsen Yan, et al. ∙ 16 ∙ share

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Self-training with progressive augmentation for unsupervised cross-domain person re-identification

Person re-identification (Re-ID) has achieved great improvement with dee...
07/31/2019 ∙ by Xinyu Zhang, et al. ∙ 15 ∙ share

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Light-Weight RefineNet for Real-Time Semantic Segmentation

We consider an important task of effective and efficient semantic image ...
10/08/2018 ∙ by Vladimir Nekrasov, et al. ∙ 12 ∙ share

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Fast Neural Architecture Search of Compact Semantic Segmentation Models via Auxiliary Cells

Automated design of architectures tailored for a specific task at hand i...
10/25/2018 ∙ by Vladimir Nekrasov, et al. ∙ 12 ∙ share

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Knowledge Adaptation for Efficient Semantic Segmentation

Both accuracy and efficiency are of significant importance to the task o...
03/12/2019 ∙ by Tong He, et al. ∙ 12 ∙ share

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Exploiting temporal consistency for real-time video depth estimation

Accuracy of depth estimation from static images has been significantly i...
08/10/2019 ∙ by Haokui Zhang, et al. ∙ 12 ∙ share

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On the General Value of Evidence, and Bilingual Scene-Text Visual Question Answering

Visual Question Answering (VQA) methods have made incredible progress, b...
02/24/2020 ∙ by Xinyu Wang, et al. ∙ 12 ∙ share

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Troy: Give Attention to Saliency and for Saliency

Saliency detection or foreground segmentation is a fundamental and impor...
08/04/2018 ∙ by Pingping Zhang, et al. ∙ 10 ∙ share

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Diagnostics in Semantic Segmentation

Over the past years, computer vision community has contributed to enormo...
09/27/2018 ∙ by Vladimir Nekrasov, et al. ∙ 10 ∙ share

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Coarse-to-fine: A RNN-based hierarchical attention model for vehicle re-identification

Vehicle re-identification is an important problem and becomes desirable ...
12/11/2018 ∙ by Xiu-Shen Wei, et al. ∙ 10 ∙ share

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Task-Aware Monocular Depth Estimation for 3D Object Detection

Monocular depth estimation enables 3D perception from a single 2D image,...
09/17/2019 ∙ by Xinlong Wang, et al. ∙ 9 ∙ share

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Deep attention-based classification network for robust depth prediction

In this paper, we present our deep attention-based classification (DABC)...
07/11/2018 ∙ by Ruibo Li, et al. ∙ 8 ∙ share

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Neighbourhood Watch: Referring Expression Comprehension via Language-guided Graph Attention Networks

The task in referring expression comprehension is to localise the object...
12/12/2018 ∙ by Peng Wang, et al. ∙ 8 ∙ share

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RERERE: Remote Embodied Referring Expressions in Real indoor Environments

One of the long-term challenges of robotics is to enable humans to commu...
04/23/2019 ∙ by Yuankai Qi, et al. ∙ 8 ∙ share

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DiverseDepth: Affine-invariant Depth Prediction Using Diverse Data

We present a method for depth estimation with monocular images, which ca...
02/03/2020 ∙ by Wei Yin, et al. ∙ 8 ∙ share

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Regularizing Proxies with Multi-Adversarial Training for Unsupervised Domain-Adaptive Semantic Segmentation

Training a semantic segmentation model requires a large amount of pixel-...
07/29/2019 ∙ by Tong Shen, et al. ∙ 7 ∙ share

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Multi-marginal Wasserstein GAN

Multiple marginal matching problem aims at learning mappings to match a ...
11/03/2019 ∙ by Jiezhang Cao, et al. ∙ 7 ∙ share

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Semi- and Weakly Supervised Directional Bootstrapping Model for Automated Skin Lesion Segmentation

Automated skin lesion segmentation on dermoscopy images is an essential ...
03/08/2019 ∙ by Yutong Xie, et al. ∙ 6 ∙ share

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Enforcing geometric constraints of virtual normal for depth prediction

Monocular depth prediction plays a crucial role in understanding 3D scen...
07/29/2019 ∙ by Yin Wei, et al. ∙ 6 ∙ share

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IR-NAS: Neural Architecture Search for Image Restoration

Recently, neural architecture search (NAS) methods have attracted much a...
09/18/2019 ∙ by Haokui Zhang, et al. ∙ 6 ∙ share

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MobileFAN: Transferring Deep Hidden Representation for Face Alignment

Facial landmark detection is a crucial prerequisite for many face analys...
08/11/2019 ∙ by Yang Zhao, et al. ∙ 5 ∙ share

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Part-Guided Attention Learning for Vehicle Re-Identification

Vehicle re-identification (Re-ID) often requires one to recognize the fi...
09/13/2019 ∙ by Xinyu Zhang, et al. ∙ 5 ∙ share

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Joint Deep Learning of Facial Expression Synthesis and Recognition

Recently, deep learning based facial expression recognition (FER) method...
02/06/2020 ∙ by Yan Yan, et al. ∙ 5 ∙ share

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Adversarial Learning with Local Coordinate Coding

Generative adversarial networks (GANs) aim to generate realistic data fr...
06/13/2018 ∙ by Jiezhang Cao, et al. ∙ 4 ∙ share

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Adaptive Importance Learning for Improving Lightweight Image Super-resolution Network

Deep neural networks have achieved remarkable success in single image su...
06/05/2018 ∙ by Lei Zhang, et al. ∙ 4 ∙ share

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Learning to predict crisp boundaries

Recent methods for boundary or edge detection built on Deep Convolutiona...
07/26/2018 ∙ by Ruoxi Deng, et al. ∙ 4 ∙ share

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Visual Question Answering as Reading Comprehension

Visual question answering (VQA) demands simultaneous comprehension of bo...
11/29/2018 ∙ by Hui Li, et al. ∙ 4 ∙ share

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From Open Set to Closed Set: Counting Objects by Spatial Divide-and-Conquer

Visual counting, a task that predicts the number of objects from an imag...
08/15/2019 ∙ by Haipeng Xiong, et al. ∙ 4 ∙ share

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Memorizing Comprehensively to Learn Adaptively: Unsupervised Cross-Domain Person Re-ID with Multi-level Memory

Unsupervised cross-domain person re-identification (Re-ID) aims to adapt...
01/13/2020 ∙ by Xinyu Zhang, et al. ∙ 4 ∙ share

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TextSR: Content-Aware Text Super-Resolution Guided by Recognition

Scene text recognition has witnessed rapid development with the advance ...
09/16/2019 ∙ by Wenjia Wang, et al. ∙ 3 ∙ share

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Multi-label Learning Based Deep Transfer Neural Network for Facial Attribute Classification

Deep Neural Network (DNN) has recently achieved outstanding performance ...
05/03/2018 ∙ by Ni Zhuang, et al. ∙ 2 ∙ share

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V-PROM: A Benchmark for Visual Reasoning Using Visual Progressive Matrices

One of the primary challenges faced by deep learning is the degree to wh...
07/29/2019 ∙ by Damien Teney, et al. ∙ 2 ∙ share

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Efficient and Accurate Arbitrary-Shaped Text Detection with Pixel Aggregation Network

Scene text detection, an important step of scene text reading systems, h...
08/16/2019 ∙ by Wenhai Wang, et al. ∙ 2 ∙ share

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A Generalized Framework for Edge-preserving and Structure-preserving Image Smoothing

Image smoothing is a fundamental procedure in applications of both compu...
07/23/2019 ∙ by Wei Liu, et al. ∙ 2 ∙ share

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Decoders Matter for Semantic Segmentation: Data-Dependent Decoding Enables Flexible Feature Aggregation

Recent semantic segmentation methods exploit encoder-decoder architectur...
03/05/2019 ∙ by Zhi Tian, et al. ∙ 1 ∙ share

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Towards End-to-End Text Spotting in Natural Scenes

Text spotting in natural scene images is of great importance for many im...
06/14/2019 ∙ by Hui Li, et al. ∙ 1 ∙ share

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Indices Matter: Learning to Index for Deep Image Matting

We show that existing upsampling operators can be unified with the notio...
08/02/2019 ∙ by Hao Lu, et al. ∙ 1 ∙ share

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Unsupervised Scale-consistent Depth and Ego-motion Learning from Monocular Video

Recent work has shown that CNN-based depth and ego-motion estimators can...
08/28/2019 ∙ by Jia-Wang Bian, et al. ∙ 1 ∙ share

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Real-time Semantic Image Segmentation via Spatial Sparsity

We propose an approach to semantic (image) segmentation that reduces the...
12/01/2017 ∙ by Zifeng Wu, et al. ∙ 0 ∙ share

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FSRNet: End-to-End Learning Face Super-Resolution with Facial Priors

Face Super-Resolution (SR) is a domain-specific super-resolution problem...
11/29/2017 ∙ by Yu Chen, et al. ∙ 0 ∙ share

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Repulsion Loss: Detecting Pedestrians in a Crowd

Detecting individual pedestrians in a crowd remains a challenging proble...
11/21/2017 ∙ by Xinlong Wang, et al. ∙ 0 ∙ share

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Chunhua Shen

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