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12 Jan 2018
Author Bio/Abstract
Recognition of visual content has been a fundamental challenge in computer vision for decades, where previous research predominantly focused on understanding visual content using a predefined yet limited vocabulary. Thanks to the recent development of deep learning techniques, researchers in both computer vision and multimedia communities are now striving to bridge vision with natural language, which can be regarded as the ultimate goal of visual understanding. We will present recent advances in exploring the synergy of visual understanding and language processing techniques, including vision-language alignment, visual captioning and commenting, visual emotion analysis, visual question answering, visual storytelling, and as well as open issues for this emerging research area.
Recognition of visual content has been a fundamental challenge in computer vision for decades, where previous research predominantly focused on understanding visual content using a predefined yet limited vocabulary. Thanks to the recent development of deep learning techniques, researchers in both computer vision and multimedia communities are now striving to bridge vision with natural language, which can be regarded as the ultimate goal of visual understanding. We will present recent advances in exploring the synergy of visual understanding and language processing techniques, including vision-language alignment, visual captioning and commenting, visual emotion analysis, visual question answering, visual storytelling, and as well as open issues for this emerging research area.
Primary Committee:
IEEE ICIP
