Ian Reid

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The University of Adelaide

Professor of Computer Science at University of Adelaide

A Theoretically Sound Upper Bound on the Triplet Loss for Improving the Efficiency of Deep Distance Metric Learning

We propose a method that substantially improves the efficiency of deep d...
04/18/2019 ∙ by Thanh-Toan Do, et al. ∙ 44 ∙ share

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Learn to Predict Sets Using Feed-Forward Neural Networks

This paper addresses the task of set prediction using deep feed-forward ...
01/30/2020 ∙ by Hamid Rezatofighi, et al. ∙ 30 ∙ share

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Meta Learning with Differentiable Closed-form Solver for Fast Video Object Segmentation

This paper tackles the problem of video object segmentation. We are spec...
09/28/2019 ∙ by Yu Liu, et al. ∙ 29 ∙ share

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Practical Visual Localization for Autonomous Driving: Why Not Filter?

A major focus of current research on place recognition is visual localiz...
11/20/2018 ∙ by Anh-Dzung Doan, et al. ∙ 28 ∙ share

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NeuRoRA: Neural Robust Rotation Averaging

Multiple rotation averaging is an essential task for structure from moti...
12/10/2019 ∙ by Pulak Purkait, et al. ∙ 27 ∙ share

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MOT20: A benchmark for multi object tracking in crowded scenes

Standardized benchmarks are crucial for the majority of computer vision ...
03/19/2020 ∙ by Patrick Dendorfer, 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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Learning to generate new indoor scenes

Deep generative models have been used in recent years to learn coherent ...
12/10/2019 ∙ by Pulak Purkait, et al. ∙ 16 ∙ share

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Depth Based Semantic Scene Completion with Position Importance Aware Loss

Semantic Scene Completion (SSC) refers to the task of inferring the 3D s...
01/29/2020 ∙ by Yu Liu, et al. ∙ 14 ∙ 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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Learning Pairwise Relationship for Multi-object Detection in Crowded Scenes

As the post-processing step for object detection, non-maximum suppressio...
01/12/2019 ∙ by Yu Liu, et al. ∙ 12 ∙ share

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Generalized Intersection over Union: A Metric and A Loss for Bounding Box Regression

Intersection over Union (IoU) is the most popular evaluation metric used...
02/25/2019 ∙ by Hamid Rezatofighi, et al. ∙ 12 ∙ share

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V2CNet: A Deep Learning Framework to Translate Videos to Commands for Robotic Manipulation

We propose V2CNet, a new deep learning framework to automatically transl...
03/23/2019 ∙ by Anh Nguyen, et al. ∙ 12 ∙ share

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An Evaluation of Feature Matchers forFundamental Matrix Estimation

Matching two images while estimating their relative geometry is a key st...
08/26/2019 ∙ by Jia-Wang Bian, et al. ∙ 12 ∙ 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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CVPR19 Tracking and Detection Challenge: How crowded can it get?

Standardized benchmarks are crucial for the majority of computer vision ...
06/10/2019 ∙ by Patrick Dendorfer, et al. ∙ 8 ∙ share

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In defense of OSVOS

As a milestone for video object segmentation, one-shot video object segm...
08/19/2019 ∙ by Yu Liu, et al. ∙ 7 ∙ share

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Pre and Post-hoc Diagnosis and Interpretation of Malignancy from Breast DCE-MRI

We propose a new method for breast cancer screening from DCE-MRI based o...
09/25/2018 ∙ by Gabriel Maicas, et al. ∙ 6 ∙ share

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Optimizable Object Reconstruction from a Single View

3D shape reconstruction from a single image is a highly ill-posed proble...
11/29/2018 ∙ by Kejie Li, et al. ∙ 4 ∙ share

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Seeing Behind Things: Extending Semantic Segmentation to Occluded Regions

Semantic segmentation and instance level segmentation made substantial p...
06/07/2019 ∙ by Pulak Purkait, et al. ∙ 4 ∙ share

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Automatic Pruning for Quantized Neural Networks

Neural network quantization and pruning are two techniques commonly used...
02/03/2020 ∙ by Luis Guerra, et al. ∙ 4 ∙ share

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Social-BiGAT: Multimodal Trajectory Forecasting using Bicycle-GAN and Graph Attention Networks

Predicting the future trajectories of multiple interacting agents in a s...
07/04/2019 ∙ by Vineet Kosaraju, et al. ∙ 3 ∙ share

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Switchable Precision Neural Networks

Instantaneous and on demand accuracy-efficiency trade-off has been recen...
02/07/2020 ∙ by Luis Guerra, et al. ∙ 3 ∙ 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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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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Parallel Attention: A Unified Framework for Visual Object Discovery through Dialogs and Queries

Recognising objects according to a pre-defined fixed set of class labels...
11/17/2017 ∙ by Bohan Zhuang, et al. ∙ 0 ∙ share

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Learning Deeply Supervised Visual Descriptors for Dense Monocular Reconstruction

Visual SLAM (Simultaneous Localization and Mapping) methods typically re...
11/16/2017 ∙ by Chamara Saroj Weerasekera, et al. ∙ 0 ∙ share

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Towards Effective Low-bitwidth Convolutional Neural Networks

This paper tackles the problem of training a deep convolutional neural n...
11/01/2017 ∙ by Bohan Zhuang, et al. ∙ 0 ∙ share

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A Bayesian Data Augmentation Approach for Learning Deep Models

Data augmentation is an essential part of the training process applied t...
10/29/2017 ∙ by Toan Tran, et al. ∙ 0 ∙ share

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AffordanceNet: An End-to-End Deep Learning Approach for Object Affordance Detection

We propose AffordanceNet, a new deep learning approach to simultaneously...
09/21/2017 ∙ by Thanh-Toan Do, et al. ∙ 0 ∙ share

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SceneCut: Joint Geometric and Object Segmentation for Indoor Scenes

This paper presents SceneCut, a novel approach to jointly discover previ...
09/21/2017 ∙ by Trung Pham, et al. ∙ 0 ∙ share

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Joint Learning of Set Cardinality and State Distribution

We present a novel approach for learning to predict sets using deep lear...
09/13/2017 ∙ by S. Hamid Rezatofighi, et al. ∙ 0 ∙ share

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Deep Subspace Clustering Networks

We present a novel deep neural network architecture for unsupervised sub...
09/08/2017 ∙ by Pan Ji, et al. ∙ 0 ∙ share

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"Maximizing rigidity" revisited: a convex programming approach for generic 3D shape reconstruction from multiple perspective views

Rigid structure-from-motion (RSfM) and non-rigid structure-from-motion (...
07/17/2017 ∙ by Pan Ji, et al. ∙ 0 ∙ share

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Non-Linear Subspace Clustering with Learned Low-Rank Kernels

In this paper, we present a kernel subspace clustering method that can h...
07/17/2017 ∙ by Pan Ji, et al. ∙ 0 ∙ share

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Care about you: towards large-scale human-centric visual relationship detection

Visual relationship detection aims to capture interactions between pairs...
05/28/2017 ∙ by Bohan Zhuang, et al. ∙ 0 ∙ share

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Weakly Supervised Semantic Segmentation Based on Web Image Co-segmentation

Training a Fully Convolutional Network (FCN) for semantic segmentation r...
05/25/2017 ∙ by Tong Shen, et al. ∙ 0 ∙ share

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Tracking the Trackers: An Analysis of the State of the Art in Multiple Object Tracking

Standardized benchmarks are crucial for the majority of computer vision ...
04/10/2017 ∙ by Laura Leal-Taixé, et al. ∙ 0 ∙ share

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Smart Mining for Deep Metric Learning

To solve deep metric learning problems and producing feature embeddings,...
04/05/2017 ∙ by Ben Harwood, et al. ∙ 0 ∙ share

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A Branch-and-Bound Algorithm for Checkerboard Extraction in Camera-Laser Calibration

We address the problem of camera-to-laser-scanner calibration using a ch...
04/04/2017 ∙ by Alireza Khosravian, et al. ∙ 0 ∙ share

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Towards Context-aware Interaction Recognition

Recognizing how objects interact with each other is a crucial task in vi...
03/18/2017 ∙ by Bohan Zhuang, et al. ∙ 0 ∙ share

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Learning Multi-level Region Consistency with Dense Multi-label Networks for Semantic Segmentation

Semantic image segmentation is a fundamental task in image understanding...
01/25/2017 ∙ by Tong Shen, et al. ∙ 0 ∙ share

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Deep Learning Features at Scale for Visual Place Recognition

The success of deep learning techniques in the computer vision domain ha...
01/18/2017 ∙ by Zetao Chen, et al. ∙ 0 ∙ share

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From Motion Blur to Motion Flow: a Deep Learning Solution for Removing Heterogeneous Motion Blur

Removing pixel-wise heterogeneous motion blur is challenging due to the ...
12/08/2016 ∙ by Dong Gong, et al. ∙ 0 ∙ share

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Attend in groups: a weakly-supervised deep learning framework for learning from web data

Large-scale datasets have driven the rapid development of deep neural ne...
11/30/2016 ∙ by Bohan Zhuang, et al. ∙ 0 ∙ share

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DeepSetNet: Predicting Sets with Deep Neural Networks

This paper addresses the task of set prediction using deep learning. Thi...
11/28/2016 ∙ by S. Hamid Rezatofighi, et al. ∙ 0 ∙ share

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RefineNet: Multi-Path Refinement Networks for High-Resolution Semantic Segmentation

Recently, very deep convolutional neural networks (CNNs) have shown outs...
11/20/2016 ∙ by Guosheng Lin, et al. ∙ 0 ∙ share

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Exploiting Temporal Information for DCNN-based Fine-Grained Object Classification

Fine-grained classification is a relatively new field that has concentra...
08/01/2016 ∙ by ZongYuan Ge, et al. ∙ 0 ∙ share

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Online Multi-Target Tracking Using Recurrent Neural Networks

We present a novel approach to online multi-target tracking based on rec...
04/13/2016 ∙ by Anton Milan, et al. ∙ 0 ∙ share

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Ian Reid

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