research
∙
06/14/2023
Improving Selective Visual Question Answering by Learning from Your Peers
Despite advances in Visual Question Answering (VQA), the ability of mode...
share
research
∙
05/11/2023
Simple Token-Level Confidence Improves Caption Correctness
The ability to judge whether a caption correctly describes an image is a...
research
∙
06/09/2022
Learn2Augment: Learning to Composite Videos for Data Augmentation in Action Recognition
We address the problem of data augmentation for video action recognition...
research
∙
04/28/2022
Reliable Visual Question Answering: Abstain Rather Than Answer Incorrectly
Machine learning has advanced dramatically, narrowing the accuracy gap t...
research
∙
01/26/2022
Learning To Recognize Procedural Activities with Distant Supervision
In this paper we consider the problem of classifying fine-grained, multi...
research
∙
12/08/2021
FLAVA: A Foundational Language And Vision Alignment Model
State-of-the-art vision and vision-and-language models rely on large-sca...
research
∙
07/27/2021
A New Split for Evaluating True Zero-Shot Action Recognition
Zero-shot action recognition is the task of classifying action categorie...
research
∙
01/18/2021
CLASTER: Clustering with Reinforcement Learning for Zero-Shot Action Recognition
Zero-shot action recognition is the task of recognizing action classes w...
research
∙
12/19/2020
SMART Frame Selection for Action Recognition
Action recognition is computationally expensive. In this paper, we addre...
research
∙
10/04/2020
Remembering for the Right Reasons: Explanations Reduce Catastrophic Forgetting
The goal of continual learning (CL) is to learn a sequence of tasks with...
research
∙
03/24/2020
TextCaps: a Dataset for Image Captioning with Reading Comprehension
Image descriptions can help visually impaired people to quickly understa...
research
∙
03/21/2020
Adversarial Continual Learning
Continual learning aims to learn new tasks without forgetting previously...
research
∙
01/10/2020
In Defense of Grid Features for Visual Question Answering
Popularized as 'bottom-up' attention, bounding box (or region) based vis...
research
∙
12/05/2019
12-in-1: Multi-Task Vision and Language Representation Learning
Much of vision-and-language research focuses on a small but diverse set ...
research
∙
11/14/2019
Iterative Answer Prediction with Pointer-Augmented Multimodal Transformers for TextVQA
Many visual scenes contain text that carries crucial information, and it...
research
∙
10/21/2019
Decoupling Representation and Classifier for Long-Tailed Recognition
The long-tail distribution of the visual world poses great challenges fo...
research
∙
06/06/2019
Uncertainty-guided Continual Learning with Bayesian Neural Networks
Continual learning aims to learn new tasks without forgetting previously...
research
∙
06/01/2019
Learning to Generate Grounded Image Captions without Localization Supervision
When generating a sentence description for an image, it frequently remai...
research
∙
04/18/2019
Towards VQA Models that can Read
Studies have shown that a dominant class of questions asked by visually ...
research
∙
04/10/2019
Drop an Octave: Reducing Spatial Redundancy in Convolutional Neural Networks with Octave Convolution
In natural images, information is conveyed at different frequencies wher...
research
∙
03/07/2019
CLEVR-Dialog: A Diagnostic Dataset for Multi-Round Reasoning in Visual Dialog
Visual Dialog is a multimodal task of answering a sequence of questions ...
research
∙
02/27/2019
Continual Learning with Tiny Episodic Memories
Learning with less supervision is a major challenge in artificial intell...
research
∙
02/21/2019
Probabilistic Neural-symbolic Models for Interpretable Visual Question Answering
We propose a new class of probabilistic neural-symbolic models, that hav...
research
∙
02/15/2019
Cycle-Consistency for Robust Visual Question Answering
Despite significant progress in Visual Question Answering over the years...
research
∙
01/11/2019
DMC-Net: Generating Discriminative Motion Cues for Fast Compressed Video Action Recognition
Motion has shown to be useful for video understanding, where motion is t...
research
∙
12/26/2018
Exploring the Challenges towards Lifelong Fact Learning
So far life-long learning (LLL) has been studied in relatively small-sca...
research
∙
12/17/2018
Grounded Video Description
Video description is one of the most challenging problems in vision and ...
research
∙
12/13/2018
Adversarial Inference for Multi-Sentence Video Description
While significant progress has been made in the image captioning task, v...
research
∙
12/02/2018
Efficient Lifelong Learning with A-GEM
In lifelong learning, the learner is presented with a sequence of tasks,...
research
∙
11/30/2018
Graph-Based Global Reasoning Networks
Globally modeling and reasoning over relations between regions can be be...
research
∙
09/06/2018
Visual Coreference Resolution in Visual Dialog using Neural Module Networks
Visual dialog entails answering a series of questions grounded in an ima...
research
∙
07/26/2018
Pythia v0.1: the Winning Entry to the VQA Challenge 2018
This document describes Pythia v0.1, the winning entry from Facebook AI ...
research
∙
06/14/2018
Selfless Sequential Learning
Sequential learning studies the problem of learning tasks in a sequence ...
research
∙
04/27/2018
Large-Scale Visual Relationship Understanding
Large scale visual understanding is challenging, as it requires a model ...
research
∙
02/15/2018
Multimodal Explanations: Justifying Decisions and Pointing to the Evidence
Deep models that are both effective and explainable are desirable in man...
research
∙
11/27/2017
Memory Aware Synapses: Learning what (not) to forget
Humans can learn in a continuous manner. Old rarely utilized knowledge c...
research
∙
11/17/2017
Attentive Explanations: Justifying Decisions and Pointing to the Evidence (Extended Abstract)
Deep models are the defacto standard in visual decision problems due to ...
research
∙
04/05/2017
Generating Descriptions with Grounded and Co-Referenced People
Learning how to generate descriptions of images or videos received major...
research
∙
03/30/2017
Speaking the Same Language: Matching Machine to Human Captions by Adversarial Training
While strong progress has been made in image captioning over the last ye...
research
∙
12/14/2016
Attentive Explanations: Justifying Decisions and Pointing to the Evidence
Deep models are the defacto standard in visual decision models due to th...
research
∙
11/30/2016
Modeling Relationships in Referential Expressions with Compositional Modular Networks
People often refer to entities in an image in terms of their relationshi...
research
∙
08/30/2016
Utilizing Large Scale Vision and Text Datasets for Image Segmentation from Referring Expressions
Image segmentation from referring expressions is a joint vision and lang...
research
∙
06/24/2016
Captioning Images with Diverse Objects
Recent captioning models are limited in their ability to scale and descr...
research
∙
06/06/2016
Multimodal Compact Bilinear Pooling for Visual Question Answering and Visual Grounding
Modeling textual or visual information with vector representations train...
research
∙
05/12/2016
Movie Description
Audio Description (AD) provides linguistic descriptions of movies and al...
research
∙
05/09/2016
Ask Your Neurons: A Deep Learning Approach to Visual Question Answering
We address a question answering task on real-world images that is set up...
research
∙
04/12/2016
Attributes as Semantic Units between Natural Language and Visual Recognition
Impressive progress has been made in the fields of computer vision and n...
research
∙
03/28/2016
Generating Visual Explanations
Clearly explaining a rationale for a classification decision to an end-u...
research
∙
03/20/2016
Segmentation from Natural Language Expressions
In this paper we approach the novel problem of segmenting an image based...
research
∙
01/07/2016