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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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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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SQuINTing at VQA Models: Interrogating VQA Models with Sub-Questions
Existing VQA datasets contain questions with varying levels of complexit...
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Trick or TReAT: Thematic Reinforcement for Artistic Typography
An approach to make text visually appealing and memorable is semantic re...
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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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Choose Your Neuron: Incorporating Domain Knowledge through Neuron-Importance
Individual neurons in convolutional neural networks supervised for image...
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Grad-CAM: Why did you say that?
We propose a technique for making Convolutional Neural Network (CNN)-bas...
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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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Counting Everyday Objects in Everyday Scenes
We are interested in counting the number of instances of object classes ...
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