Damien Teney | DeepAI

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∙ 08/30/2023

Learning Diverse Features in Vision Transformers for Improved Generalization

Deep learning models often rely only on a small set of features even whe...

0 Armand Mihai Nicolicioiu, et al. ∙

∙ 05/25/2023

Candidate Set Re-ranking for Composed Image Retrieval with Dual Multi-modal Encoder

Composed image retrieval aims to find an image that best matches a given...

0 Zheyuan Liu, et al. ∙

∙ 05/21/2023

A Symbolic Framework for Systematic Evaluation of Mathematical Reasoning with Transformers

Whether Transformers can learn to apply symbolic rules and generalise to...

0 Jordan Meadows, et al. ∙

∙ 03/29/2023

Bi-directional Training for Composed Image Retrieval via Text Prompt Learning

Composed image retrieval searches for a target image based on a multi-mo...

0 Zheyuan Liu, et al. ∙

∙ 11/04/2022

SelecMix: Debiased Learning by Contradicting-pair Sampling

Neural networks trained with ERM (empirical risk minimization) sometimes...

0 Inwoo Hwang, et al. ∙

∙ 08/09/2021

Image Retrieval on Real-life Images with Pre-trained Vision-and-Language Models

We extend the task of composed image retrieval, where an input query con...

0 Zheyuan Liu, et al. ∙

∙ 04/07/2021

Beyond Question-Based Biases: Assessing Multimodal Shortcut Learning in Visual Question Answering

We introduce an evaluation methodology for visual question answering (VQ...

0 Corentin Dancette, et al. ∙

∙ 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. ∙

∙ 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. ∙

∙ 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. ∙

∙ 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. ∙

∙ 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. ∙

∙ 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. ∙

∙ 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. ∙

∙ 11/20/2017

Vision-and-Language Navigation: Interpreting visually-grounded navigation instructions in real environments

A robot that can carry out a natural-language instruction has been a dre...

0 Peter Anderson, et al. ∙

∙ 08/09/2017

Tips and Tricks for Visual Question Answering: Learnings from the 2017 Challenge

This paper presents a state-of-the-art model for visual question answeri...

0 Damien Teney, et al. ∙

∙ 07/25/2017

Bottom-Up and Top-Down Attention for Image Captioning and Visual Question Answering

Top-down visual attention mechanisms have been used extensively in image...

0 Peter Anderson, et al. ∙

∙ 11/17/2016

Zero-Shot Visual Question Answering

Part of the appeal of Visual Question Answering (VQA) is its promise to ...

0 Damien Teney, et al. ∙

∙ 09/19/2016

Graph-Structured Representations for Visual Question Answering

This paper proposes to improve visual question answering (VQA) with stru...

0 Damien Teney, et al. ∙

∙ 01/27/2016

Learning to Extract Motion from Videos in Convolutional Neural Networks

This paper shows how to extract dense optical flow from videos with a co...

0 Damien Teney, et al. ∙

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