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08/03/2022
TAG: Boosting Text-VQA via Text-aware Visual Question-answer Generation
Text-VQA aims at answering questions that require understanding the text...
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04/23/2022
Can domain adaptation make object recognition work for everyone?
Despite the rapid progress in deep visual recognition, modern computer v...
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12/14/2021
CLIP-Lite: Information Efficient Visual Representation Learning from Textual Annotations
We propose CLIP-Lite, an information efficient method for visual represe...
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12/01/2021
PreViTS: Contrastive Pretraining with Video Tracking Supervision
Videos are a rich source for self-supervised learning (SSL) of visual re...
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07/16/2021
Align before Fuse: Vision and Language Representation Learning with Momentum Distillation
Large-scale vision and language representation learning has shown promis...
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12/08/2020
CASTing Your Model: Learning to Localize Improves Self-Supervised Representations
Recent advances in self-supervised learning (SSL) have largely closed th...
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10/20/2020
SOrT-ing VQA Models : Contrastive Gradient Learning for Improved Consistency
Recent research in Visual Question Answering (VQA) has revealed state-of...
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01/20/2020
SQuINTing at VQA Models: Interrogating VQA Models with Sub-Questions
Existing VQA datasets contain questions with varying levels of complexit...
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03/19/2019
Trick or TReAT: Thematic Reinforcement for Artistic Typography
An approach to make text visually appealing and memorable is semantic re...
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02/11/2019
Taking a HINT: Leveraging Explanations to Make Vision and Language Models More Grounded
Many vision and language models suffer from poor visual grounding - ofte...
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08/08/2018
Choose Your Neuron: Incorporating Domain Knowledge through Neuron-Importance
Individual neurons in convolutional neural networks supervised for image...
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11/22/2016
Grad-CAM: Why did you say that?
We propose a technique for making Convolutional Neural Network (CNN)-bas...
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10/07/2016
Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization
We propose a technique for producing "visual explanations" for decisions...
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04/12/2016