b'Philip Torr'

research

∙ 09/12/2023

Exploring Non-additive Randomness on ViT against Query-Based Black-Box Attacks

Deep Neural Networks can be easily fooled by small and imperceptible per...

0 Jindong Gu, et al. ∙

research

∙ 08/03/2023

Neural Collapse Terminus: A Unified Solution for Class Incremental Learning and Its Variants

How to enable learnability for new classes while keeping the capability ...

0 Yibo Yang, et al. ∙

research

∙ 07/24/2023

A Systematic Survey of Prompt Engineering on Vision-Language Foundation Models

Prompt engineering is a technique that involves augmenting a large pre-t...

0 Jindong Gu, et al. ∙

research

∙ 07/21/2023

OxfordTVG-HIC: Can Machine Make Humorous Captions from Images?

This paper presents OxfordTVG-HIC (Humorous Image Captions), a large-sca...

0 Runjia Li, et al. ∙

research

∙ 06/29/2023

ReMaX: Relaxing for Better Training on Efficient Panoptic Segmentation

This paper presents a new mechanism to facilitate the training of mask t...

0 Shuyang Sun, et al. ∙

research

∙ 06/14/2023

Reliable Evaluation of Adversarial Transferability

Adversarial examples (AEs) with small adversarial perturbations can misl...

0 Wenqian Yu, et al. ∙

research

∙ 06/03/2023

Benchmarking Robustness of Adaptation Methods on Pre-trained Vision-Language Models

Various adaptation methods, such as LoRA, prompts, and adapters, have be...

0 Shuo Chen, et al. ∙

research

∙ 05/27/2023

Graph Inductive Biases in Transformers without Message Passing

Transformers for graph data are increasingly widely studied and successf...

0 Liheng Ma, et al. ∙

research

∙ 05/17/2023

Provably Correct Physics-Informed Neural Networks

Recent work provides promising evidence that Physics-informed neural net...

0 Francisco Eiras, et al. ∙

research

∙ 05/16/2023

Online Continual Learning Without the Storage Constraint

Online continual learning (OCL) research has primarily focused on mitiga...

0 Ameya Prabhu, et al. ∙

research

∙ 04/17/2023

Towards Robust Prompts on Vision-Language Models

With the advent of vision-language models (VLMs) that can perform in-con...

0 Jindong Gu, et al. ∙

research

∙ 03/21/2023

Influencer Backdoor Attack on Semantic Segmentation

When a small number of poisoned samples are injected into the training d...

0 Haoheng Lan, et al. ∙

research

∙ 03/20/2023

Reliability in Semantic Segmentation: Are We on the Right Track?

Motivated by the increasing popularity of transformers in computer visio...

0 Pau de Jorge, et al. ∙

research

∙ 02/07/2023

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

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

0 Zitong Yu, et al. ∙

research

∙ 02/06/2023

Neural Collapse Inspired Feature-Classifier Alignment for Few-Shot Class Incremental Learning

Few-shot class-incremental learning (FSCIL) has been a challenging probl...

0 Yibo Yang, et al. ∙

research

∙ 12/21/2022

Not Just Pretty Pictures: Text-to-Image Generators Enable Interpretable Interventions for Robust Representations

Neural image classifiers are known to undergo severe performance degrada...

0 Jianhao Yuan, et al. ∙

research

∙ 12/11/2022

General Adversarial Defense Against Black-box Attacks via Pixel Level and Feature Level Distribution Alignments

Deep Neural Networks (DNNs) are vulnerable to the black-box adversarial ...

0 Xiaogang Xu, et al. ∙

research

∙ 11/29/2022

LUMix: Improving Mixup by Better Modelling Label Uncertainty

Modern deep networks can be better generalized when trained with noisy s...

0 Shuyang Sun, et al. ∙

research

∙ 09/26/2022

Diversified Dynamic Routing for Vision Tasks

Deep learning models for vision tasks are trained on large datasets unde...

7 Botos Csaba, et al. ∙

research

∙ 07/25/2022

SegPGD: An Effective and Efficient Adversarial Attack for Evaluating and Boosting Segmentation Robustness

Deep neural network-based image classifications are vulnerable to advers...

0 Jindong Gu, et al. ∙

research

∙ 07/14/2022

Universal Adaptive Data Augmentation

Existing automatic data augmentation (DA) methods either ignore updating...

0 Xiaogang Xu, et al. ∙

research

∙ 07/13/2022

Collaborative Quantization Embeddings for Intra-Subject Prostate MR Image Registration

Image registration is useful for quantifying morphological changes in lo...

0 Ziyi Shen, et al. ∙

research

∙ 04/18/2022

Unsupervised Contrastive Domain Adaptation for Semantic Segmentation

Semantic segmentation models struggle to generalize in the presence of d...

0 Feihu Zhang, et al. ∙

research

∙ 04/18/2022

MP2: A Momentum Contrast Approach for Recommendation with Pointwise and Pairwise Learning

Binary pointwise labels (aka implicit feedback) are heavily leveraged by...

0 Menghan Wang, et al. ∙

research

∙ 03/15/2022

Task-Agnostic Robust Representation Learning

It has been reported that deep learning models are extremely vulnerable ...

1 A. Tuan Nguyen, et al. ∙

research

∙ 03/08/2022

Language Matters: A Weakly Supervised Pre-training Approach for Scene Text Detection and Spotting

Recently, Vision-Language Pre-training (VLP) techniques have greatly ben...

0 Chuhui Xue, et al. ∙

research

∙ 02/17/2022

Gradients without Backpropagation

Using backpropagation to compute gradients of objective functions for op...

0 Atılım Güneş Baydin, et al. ∙

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...

0 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...

0 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...

0 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...

0 Jie-Neng Chen, et al. ∙

research

∙ 08/03/2021

Vision Transformer with Progressive Sampling

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

0 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...

0 Botos Csaba, et al. ∙

research

∙ 07/17/2021

Implicit Communication as Minimum Entropy Coupling

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

3 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 ...

0 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...

0 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...

5 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...

0 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. ...

15 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,...

0 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...

11 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...

13 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...

0 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 ...

24 Zhengzhe Liu, et al. ∙

research

∙ 11/29/2019

Domain-invariant Stereo Matching Networks

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

4 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...

2 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...

2 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...

0 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...

0 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...

0 Måns Larsson, et al. ∙

Philip Torr

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