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09/07/2023
Better Practices for Domain Adaptation
Distribution shifts are all too common in real-world applications of mac...
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03/25/2023
Fairness meets Cross-Domain Learning: a new perspective on Models and Metrics
Deep learning-based recognition systems are deployed at scale for severa...
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12/11/2022
Accelerating Self-Supervised Learning via Efficient Training Strategies
Recently the focus of the computer vision community has shifted from exp...
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06/10/2022
Fisher SAM: Information Geometry and Sharpness Aware Minimisation
Recent sharpness-aware minimisation (SAM) is known to find flat minima w...
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04/15/2022
Pushing the Limits of Simple Pipelines for Few-Shot Learning: External Data and Fine-Tuning Make a Difference
Few-shot learning (FSL) is an important and topical problem in computer ...
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03/05/2022
Meta Mirror Descent: Optimiser Learning for Fast Convergence
Optimisers are an essential component for training machine learning mode...
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11/22/2021
Why Do Self-Supervised Models Transfer? Investigating the Impact of Invariance on Downstream Tasks
Self-supervised learning is a powerful paradigm for representation learn...
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10/18/2021
Self-Supervised Representation Learning: Introduction, Advances and Challenges
Self-supervised representation learning methods aim to provide powerful ...
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05/18/2021
Towards Unsupervised Sketch-based Image Retrieval
Current supervised sketch-based image retrieval (SBIR) methods achieve e...
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03/25/2021
Vectorization and Rasterization: Self-Supervised Learning for Sketch and Handwriting
Self-supervised learning has gained prominence due to its efficacy at le...
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02/27/2021
Searching for Robustness: Loss Learning for Noisy Classification Tasks
We present a "learning to learn" approach for automatically constructing...
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01/27/2021
FedH2L: Federated Learning with Model and Statistical Heterogeneity
Federated learning (FL) enables distributed participants to collectively...
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12/10/2020
Tensor Composition Net for Visual Relationship Prediction
We present a novel Tensor Composition Network (TCN) to predict visual re...
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11/26/2020
How Well Do Self-Supervised Models Transfer?
Self-supervised visual representation learning has seen huge progress in...
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07/07/2020
On Learning Semantic Representations for Million-Scale Free-Hand Sketches
In this paper, we study learning semantic representations for million-sc...
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06/22/2020
Don't Wait, Just Weight: Improving Unsupervised Representations by Learning Goal-Driven Instance Weights
In the absence of large labelled datasets, self-supervised learning tech...
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03/11/2020
Online Meta-Critic Learning for Off-Policy Actor-Critic Methods
Off-Policy Actor-Critic (Off-PAC) methods have proven successful in a va...
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03/02/2020
Unlimited Resolution Image Generation with R2D2-GANs
In this paper we present a novel simulation technique for generating hig...
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02/24/2020
Sketch Less for More: On-the-Fly Fine-Grained Sketch Based Image Retrieval
Fine-grained sketch-based image retrieval (FG-SBIR) addresses the proble...
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02/21/2020
Fine-Grained Instance-Level Sketch-Based Video Retrieval
Existing sketch-analysis work studies sketches depicting static objects ...
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02/19/2020
Distance-Based Regularisation of Deep Networks for Fine-Tuning
We investigate approaches to regularisation during fine-tuning of deep n...
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01/08/2020
Deep Learning for Free-Hand Sketch: A Survey and A Toolbox
Free-hand sketches are highly illustrative, and have been widely used by...
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10/17/2019
Deep clustering with concrete k-means
We address the problem of simultaneously learning a k-means clustering a...
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09/25/2019
On Understanding Knowledge Graph Representation
Many methods have been developed to represent knowledge graph data, whic...
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07/29/2019
Goal-Driven Sequential Data Abstraction
Automatic data abstraction is an important capability for both benchmark...
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07/14/2019
Measuring the Transferability of Adversarial Examples
Adversarial examples are of wide concern due to their impact on the reli...
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05/09/2019
Frustratingly Easy Person Re-Identification: Generalizing Person Re-ID in Practice
Contemporary person re-identification (Re-ID) methods usually require ac...
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02/19/2019
Investigating Generalisation in Continuous Deep Reinforcement Learning
Deep Reinforcement Learning has shown great success in a variety of cont...
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01/31/2019
Episodic Training for Domain Generalization
Domain generalization (DG) is the challenging and topical problem of lea...
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01/31/2019
Feature-Critic Networks for Heterogeneous Domain Generalization
The well known domain shift issue causes model performance to degrade wh...
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01/28/2019
TuckER: Tensor Factorization for Knowledge Graph Completion
Knowledge graphs are structured representations of real world facts. How...
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12/06/2018
Disjoint Label Space Transfer Learning with Common Factorised Space
In this paper, a unified approach is presented to transfer learning that...
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11/17/2018
Deep Comparison: Relation Columns for Few-Shot Learning
Few-shot deep learning is a topical challenge area for scaling visual re...
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09/29/2018
Dynamic Ensemble Active Learning: A Non-Stationary Bandit with Expert Advice
Active learning aims to reduce annotation cost by predicting which sampl...
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08/21/2018
Hypernetwork Knowledge Graph Embeddings
Knowledge graphs are large graph-structured databases of facts, which ty...
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08/07/2018
Deep Factorised Inverse-Sketching
Modelling human free-hand sketches has become topical recently, driven b...
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08/07/2018
Universal Perceptual Grouping
In this work we aim to develop a universal sketch grouper. That is, a gr...
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06/19/2018
Deep Neural Decision Trees
Deep neural networks have been proven powerful at processing perceptual ...
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04/30/2018
Sketch-a-Classifier: Sketch-based Photo Classifier Generation
Contemporary deep learning techniques have made image recognition a reas...
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04/13/2018
Learning Deep Sketch Abstraction
Human free-hand sketches have been studied in various contexts including...
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04/04/2018
SketchMate: Deep Hashing for Million-Scale Human Sketch Retrieval
We propose a deep hashing framework for sketch retrieval that, for the f...
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03/24/2018
Multi-Level Factorisation Net for Person Re-Identification
Key to effective person re-identification (Re-ID) is modelling discrimin...
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03/16/2018
Inverse Visual Question Answering: A New Benchmark and VQA Diagnosis Tool
In recent years, visual question answering (VQA) has become topical. The...
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11/22/2017
The Devil is in the Middle: Exploiting Mid-level Representations for Cross-Domain Instance Matching
Many vision problems require matching images of object instances across ...
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11/16/2017
Deep Matching Autoencoders
Increasingly many real world tasks involve data in multiple modalities o...
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11/16/2017
Learning to Compare: Relation Network for Few-Shot Learning
We present a conceptually simple, flexible, and general framework for fe...
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10/10/2017
iVQA: Inverse Visual Question Answering
In recent years, visual question answering (VQA) has become topical as a...
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10/09/2017
Deeper, Broader and Artier Domain Generalization
The problem of domain generalization is to learn from multiple training ...
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08/08/2017
Weakly Supervised Image Annotation and Segmentation with Objects and Attributes
We propose to model complex visual scenes using a non-parametric Bayesia...
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07/30/2017