Anton van den Hengel

research

∙ 08/22/2023

Domain Generalization via Rationale Invariance

This paper offers a new perspective to ease the challenge of domain gene...

0 Liang Chen, et al. ∙

research

∙ 06/12/2023

Provably Efficient Bayesian Optimization with Unbiased Gaussian Process Hyperparameter Estimation

Gaussian process (GP) based Bayesian optimization (BO) is a powerful met...

0 Huong Ha, et al. ∙

research

∙ 04/05/2023

Knowledge Combination to Learn Rotated Detection Without Rotated Annotation

Rotated bounding boxes drastically reduce output ambiguity of elongated ...

5 Tianyu Zhu, et al. ∙

research

∙ 03/30/2023

Adaptive Cross Batch Normalization for Metric Learning

Metric learning is a fundamental problem in computer vision whereby a mo...

9 Thalaiyasingam Ajanthan, et al. ∙

research

∙ 03/03/2023

Learning Common Rationale to Improve Self-Supervised Representation for Fine-Grained Visual Recognition Problems

Self-supervised learning (SSL) strategies have demonstrated remarkable p...

30 Yangyang Shu, et al. ∙

research

∙ 02/27/2023

BaLi-RF: Bandlimited Radiance Fields for Dynamic Scene Modeling

Reasoning the 3D structure of a non-rigid dynamic scene from a single mo...

5 Sameera Ramasinghe, et al. ∙

research

∙ 12/22/2022

Understanding and Improving the Role of Projection Head in Self-Supervised Learning

Self-supervised learning (SSL) aims to produce useful feature representa...

4 Kartik Gupta, et al. ∙

research

∙ 06/13/2022

Confident Sinkhorn Allocation for Pseudo-Labeling

Semi-supervised learning is a critical tool in reducing machine learning...

19 Vu Nguyen, et al. ∙

research

∙ 04/25/2022

PointInst3D: Segmenting 3D Instances by Points

The current state-of-the-art methods in 3D instance segmentation typical...

2 Tong He, et al. ∙

research

∙ 03/21/2022

CNN Attention Guidance for Improved Orthopedics Radiographic Fracture Classification

Convolutional neural networks (CNNs) have gained significant popularity ...

8 Zhibin Liao, et al. ∙

research

∙ 03/04/2022

Distributionally Robust Bayesian Optimization with φ-divergences

The study of robustness has received much attention due to its inevitabi...

10 Hisham Husain, et al. ∙

research

∙ 02/22/2022

Retrieval Augmented Classification for Long-Tail Visual Recognition

We introduce Retrieval Augmented Classification (RAC), a generic approac...

4 Alexander Long, et al. ∙

research

∙ 02/21/2022

Learning Bayesian Sparse Networks with Full Experience Replay for Continual Learning

Continual Learning (CL) methods aim to enable machine learning models to...

9 Dong Gong, et al. ∙

research

∙ 01/19/2022

Poseur: Direct Human Pose Regression with Transformers

We propose a direct, regression-based approach to 2D human pose estimati...

4 Weian Mao, et al. ∙

research

∙ 07/18/2021

Dynamic Convolution for 3D Point Cloud Instance Segmentation

We propose an approach to instance segmentation from 3D point clouds bas...

13 Tong He, et al. ∙

research

∙ 01/15/2021

Reasoning over Vision and Language: Exploring the Benefits of Supplemental Knowledge

The limits of applicability of vision-and-language models are defined by...

6 Violetta Shevchenko, et al. ∙

research

∙ 12/05/2020

Deep Multi-task Learning for Depression Detection and Prediction in Longitudinal Data

Depression is among the most prevalent mental disorders, affecting milli...

36 Guansong Pang, et al. ∙

research

∙ 11/26/2020

DyCo3D: Robust Instance Segmentation of 3D Point Clouds through Dynamic Convolution

Previous top-performing approaches for point cloud instance segmentation...

0 Tong He, et al. ∙

research

∙ 09/15/2020

Deep Reinforcement Learning for Unknown Anomaly Detection

We address a critical yet largely unsolved anomaly detection problem, in...

40 Guansong Pang, et al. ∙

research

∙ 07/29/2020

Object-and-Action Aware Model for Visual Language Navigation

Vision-and-Language Navigation (VLN) is unique in that it requires turni...

2 Yuankai Qi, et al. ∙

research

∙ 07/06/2020

Deep Learning for Anomaly Detection: A Review

Anomaly detection, a.k.a. outlier detection, has been a lasting yet acti...

59 Guansong Pang, et al. ∙

research

∙ 06/01/2020

Structured Multimodal Attentions for TextVQA

Text based Visual Question Answering (TextVQA) is a recently raised chal...

12 Chenyu Gao, et al. ∙

research

∙ 05/04/2020

Visual Question Answering with Prior Class Semantics

We present a novel mechanism to embed prior knowledge in a model for vis...

5 Violetta Shevchenko, et al. ∙

research

∙ 04/20/2020

Learning What Makes a Difference from Counterfactual Examples and Gradient Supervision

One of the primary challenges limiting the applicability of deep learnin...

2 Damien Teney, et al. ∙

research

∙ 03/15/2020

Self-trained Deep Ordinal Regression for End-to-End Video Anomaly Detection

Video anomaly detection is of critical practical importance to a variety...

1 Guansong Pang, et al. ∙

research

∙ 02/24/2020

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

Visual Question Answering (VQA) methods have made incredible progress, b...

12 Xinyu Wang, et al. ∙

research

∙ 01/08/2020

Learning to Zoom-in via Learning to Zoom-out: Real-world Super-resolution by Generating and Adapting Degradation

Most learning-based super-resolution (SR) methods aim to recover high-re...

15 Dong Gong, et al. ∙

research

∙ 11/19/2019

Deep Anomaly Detection with Deviation Networks

Although deep learning has been applied to successfully address many dat...

17 Guansong Pang, et al. ∙

research

∙ 10/30/2019

Weakly-supervised Deep Anomaly Detection with Pairwise Relation Learning

This paper studies a rarely explored but critical anomaly detection prob...

19 Guansong Pang, et al. ∙

research

∙ 09/30/2019

On Incorporating Semantic Prior Knowlegde in Deep Learning Through Embedding-Space Constraints

The knowledge that humans hold about a problem often extends far beyond ...

52 Damien Teney, et al. ∙

research

∙ 07/29/2019

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...

2 Damien Teney, et al. ∙

research

∙ 05/14/2019

An Effective Two-Branch Model-Based Deep Network for Single Image Deraining

Removing rain effects from an image automatically has many applications ...

6 Yinglong Wang, et al. ∙

research

∙ 04/23/2019

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

Ghosting artifacts caused by moving objects or misalignments is a key ch...

16 Qingsen Yan, et al. ∙

research

∙ 04/23/2019

RERERE: Remote Embodied Referring Expressions in Real indoor Environments

One of the long-term challenges of robotics is to enable humans to commu...

8 Yuankai Qi, et al. ∙

research

∙ 04/06/2019

Reinforcement Learning with Attention that Works: A Self-Supervised Approach

Attention models have had a significant positive impact on deep learning...

14 Anthony Manchin, et al. ∙

research

∙ 04/05/2019

Actively Seeking and Learning from Live Data

One of the key limitations of traditional machine learning methods is th...

34 Damien Teney, et al. ∙

research

∙ 04/04/2019

Memorizing Normality to Detect Anomaly: Memory-augmented Deep Autoencoder for Unsupervised Anomaly Detection

Deep autoencoder has been extensively used for anomaly detection. Traini...

34 Dong Gong, et al. ∙

research

∙ 12/16/2018

What's to know? Uncertainty as a Guide to Asking Goal-oriented Questions

One of the core challenges in Visual Dialogue problems is asking the que...

0 Ehsan Abbasnejad, et al. ∙

research

∙ 12/16/2018

An Active Information Seeking Model for Goal-oriented Vision-and-Language Tasks

As Computer Vision algorithms move from passive analysis of pixels to ac...

0 Ehsan Abbasnejad, et al. ∙

research

∙ 12/12/2018

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

The task in referring expression comprehension is to localise the object...

8 Peng Wang, et al. ∙

research

∙ 11/29/2018

Visual Question Answering as Reading Comprehension

Visual question answering (VQA) demands simultaneous comprehension of bo...

4 Hui Li, et al. ∙

research

∙ 10/23/2018

End-to-End Diagnosis and Segmentation Learning from Cardiac Magnetic Resonance Imaging

Cardiac magnetic resonance (CMR) is used extensively in the diagnosis an...

4 Gerard Snaauw, et al. ∙

research

∙ 10/12/2018

MPTV: Matching Pursuit Based Total Variation Minimization for Image Deconvolution

Total variation (TV) regularization has proven effective for a range of ...

0 Dong Gong, et al. ∙

research

∙ 08/30/2018

Towards Effective Deep Embedding for Zero-Shot Learning

Zero-shot learning (ZSL) attempts to recognize visual samples of unseen ...

0 Lei Zhang, et al. ∙

research

∙ 06/05/2018

Adaptive Importance Learning for Improving Lightweight Image Super-resolution Network

Deep neural networks have achieved remarkable success in single image su...

4 Lei Zhang, et al. ∙

research

∙ 04/10/2018

Learning an Optimizer for Image Deconvolution

As an integral component of blind image deblurring, non-blind deconvolut...

0 Dong Gong, et al. ∙

research

∙ 12/01/2017

Real-time Semantic Image Segmentation via Spatial Sparsity

We propose an approach to semantic (image) segmentation that reduces the...

0 Zifeng Wu, et al. ∙

research

∙ 11/22/2017

Visual Question Answering as a Meta Learning Task

The predominant approach to Visual Question Answering (VQA) demands that...

0 Damien Teney, et al. ∙

research

∙ 11/21/2017

Asking the Difficult Questions: Goal-Oriented Visual Question Generation via Intermediate Rewards

Despite significant progress in a variety of vision-and-language problem...

0 Junjie Zhang, et al. ∙

research

∙ 11/21/2017

Are You Talking to Me? Reasoned Visual Dialog Generation through Adversarial Learning

The Visual Dialogue task requires an agent to engage in a conversation a...

0 Qi Wu, et al. ∙

Anton van den Hengel

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