2022
IJCAI
IJCAI 2022
Visual Emotion Representation Learning via Emotion-Aware Pre-training
Abstract
Despite recent progress in deep learning, visual emotion recognition remains a challenging problem due to ambiguity of emotion perception, diverse concepts related to visual emotion and lack of large-scale annotated dataset. In this paper, we present a large-scale multimodal pre-training method to learn visual emotion representation by aligning emotion, object, attribute triplet with a contrastive loss. We conduct our pre-training on a large web dataset with noisy tags and fine-tune on visual emotion classification datasets. Our method achieves state-of-the-art performance for visual emotion classification.
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Interdisciplinary Bridge
β Artificial Intelligence and Deep Learning and Machine Learning
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Keyword Pioneer
β visual emotion recognition
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Cross-Pollinator
β Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Speech & Audio
Authors
Topics
Artificial Intelligence > Core AI > Multimodal Learning
Machine Learning > Learning Types > Self-Supervised Learning
Deep Learning > Techniques > Pretraining
Interdisciplinary > Social > Affective Computing
Deep Learning > Learning Types > Self-Supervised Learning
Deep Learning > Learning Types > Multimodal Learning