b'Philip Torr'

research

∙ 12/09/2021

Mimicking the Oracle: An Initial Phase Decorrelation Approach for Class Incremental Learning

Class Incremental Learning (CIL) aims at learning a multi-class classifi...

Yujun Shi, et al. ∙

research

∙ 11/23/2021

PhysFormer: Facial Video-based Physiological Measurement with Temporal Difference Transformer

Remote photoplethysmography (rPPG), which aims at measuring heart activi...

Zitong Yu, et al. ∙

research

∙ 11/22/2021

Adversarial Examples on Segmentation Models Can be Easy to Transfer

Deep neural network-based image classification can be misled by adversar...

Jindong Gu, et al. ∙

research

∙ 11/18/2021

TransMix: Attend to Mix for Vision Transformers

Mixup-based augmentation has been found to be effective for generalizing...

Jie-Neng Chen, et al. ∙

research

∙ 08/03/2021

Vision Transformer with Progressive Sampling

Transformers with powerful global relation modeling abilities have been ...

Xiaoyu Yue, et al. ∙

research

∙ 08/02/2021

Multilevel Knowledge Transfer for Cross-Domain Object Detection

Domain shift is a well known problem where a model trained on a particul...

Botos Csaba, et al. ∙

research

∙ 07/17/2021

Implicit Communication as Minimum Entropy Coupling

In many common-payoff games, achieving good performance requires players...

Samuel Sokota, et al. ∙

research

∙ 07/13/2021

Visual Parser: Representing Part-whole Hierarchies with Transformers

Human vision is able to capture the part-whole hierarchical information ...

Shuyang Sun, et al. ∙

research

∙ 11/24/2020

Learning to Sample the Most Useful Training Patches from Images

Some image restoration tasks like demosaicing require difficult training...

Shuyang Sun, et al. ∙

research

∙ 10/28/2020

Class-Agnostic Segmentation Loss and Its Application to Salient Object Detection and Segmentation

In this paper we present a novel loss function, called class-agnostic se...

Angira Sharma, et al. ∙

research

∙ 10/10/2020

Diagnosing and Preventing Instabilities in Recurrent Video Processing

Recurrent models are becoming a popular choice for video enhancement tas...

Thomas Tanay, et al. ∙

research

∙ 09/16/2020

HOTA: A Higher Order Metric for Evaluating Multi-Object Tracking

Multi-Object Tracking (MOT) has been notoriously difficult to evaluate. ...

Jonathon Luiten, et al. ∙

research

∙ 08/21/2020

Many-shot from Low-shot: Learning to Annotate using Mixed Supervision for Object Detection

Object detection has witnessed significant progress by relying on large,...

Carlo Biffi, et al. ∙

research

∙ 05/14/2020

Simulation-Based Inference for Global Health Decisions

The COVID-19 pandemic has highlighted the importance of in-silico epidem...

Christian Schroeder de Witt, et al. ∙

research

∙ 03/14/2020

Deep Multi-Agent Reinforcement Learning for Decentralized Continuous Cooperative Control

Deep multi-agent reinforcement learning (MARL) holds the promise of auto...

Christian Schroeder de Witt, et al. ∙

research

∙ 02/19/2020

Using Hindsight to Anchor Past Knowledge in Continual Learning

In continual learning, the learner faces a stream of data whose distribu...

Arslan Chaudhry, et al. ∙

research

∙ 02/01/2020

Global Texture Enhancement for Fake Face Detection in the Wild

Generative Adversarial Networks (GANs) can generate realistic fake face ...

Zhengzhe Liu, et al. ∙

research

∙ 11/29/2019

Domain-invariant Stereo Matching Networks

State-of-the-art stereo matching networks have difficulties in generaliz...

Feihu Zhang, et al. ∙

research

∙ 07/08/2019

Etalumis: Bringing Probabilistic Programming to Scientific Simulators at Scale

Probabilistic programming languages (PPLs) are receiving widespread atte...

Atılım Güneş Baydin, et al. ∙

research

∙ 06/20/2019

Let's Take This Online: Adapting Scene Coordinate Regression Network Predictions for Online RGB-D Camera Relocalisation

Many applications require a camera to be relocalised online, without exp...

Tommaso Cavallari, et al. ∙

research

∙ 04/02/2019

Res2Net: A New Multi-scale Backbone Architecture

Representing features at multiple scales is of great importance for nume...

Shang-Hua Gao, et al. ∙

research

∙ 03/26/2018

Long-term Tracking in the Wild: A Benchmark

We introduce a new video dataset and benchmark to assess single-object t...

Jack Valmadre, et al. ∙

research

∙ 01/24/2017

Learning Arbitrary Pairwise Potentials in CRFs for Semantic Segmentation

Are we using the right potential functions in the Conditional Random Fie...

Måns Larsson, et al. ∙

research

∙ 12/07/2016

Bottom-Up Top-Down Cues for Weakly-Supervised Semantic Segmentation

We consider the task of learning a classifier for semantic segmentation ...

Qinbin Hou, et al. ∙

research

∙ 11/25/2016

Online Real-time Multiple Spatiotemporal Action Localisation and Prediction

We present a deep-learning framework for real-time multiple spatio-tempo...

Gurkirt Singh, et al. ∙

research

∙ 11/15/2016

Deeply supervised salient object detection with short connections

Recent progress on saliency detection is substantial, benefiting mostly ...

Qibin Hou, et al. ∙

research

∙ 03/18/2016

Learning to Navigate the Energy Landscape

In this paper, we present a novel and efficient architecture for address...

Julien Valentin, et al. ∙

research

∙ 01/10/2016

Joint Object-Material Category Segmentation from Audio-Visual Cues

It is not always possible to recognise objects and infer material proper...

Anurag Arnab, et al. ∙

research

∙ 12/04/2015

Staple: Complementary Learners for Real-Time Tracking

Correlation Filter-based trackers have recently achieved excellent perfo...

Luca Bertinetto, et al. ∙

research

∙ 12/03/2015

Prototypical Priors: From Improving Classification to Zero-Shot Learning

Recent works on zero-shot learning make use of side information such as ...

Saumya Jetley, et al. ∙

research

∙ 04/20/2014

Efficient Semidefinite Branch-and-Cut for MAP-MRF Inference

We propose a Branch-and-Cut (B&C) method for solving general MAP-MRF inf...

Peng Wang, et al. ∙

research

∙ 10/16/2013

ImageSpirit: Verbal Guided Image Parsing

Humans describe images in terms of nouns and adjectives while algorithms...

Ming-Ming Cheng, et al. ∙

Philip Torr

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