About Victor Escorcia Victor Escorcia Ph.D., Electrical and Computer Engineering Computer Vision artificial intelligence Video Understanding Deep generative models Mobile AI Research Scientist committed to innovating AI agents to empower creativity and increase productivity. Passionate about developing cutting-edge AI applications involving video understanding and creative storytelling. I have a wide range of research and engineering interests from on-device AI to General AI. Reach out! Events Presented Events Jun 9 - Jun 15, 2019 Efficient Localization of Human Actions and Moments in Videos Victor Escorcia, Ph.D., Electrical and Computer Engineering Jun 11, 15:00 - 16:00 B3 L5 R5220 Computer Vision machine learning artificial intelligence Abstract We are stumbling across a video tsunami flooding our communication channels. The ubiquity of digital cameras and social networks has increased the amount of visual media content generated and shared by people, in particular videos. Cisco reports that 82% of the internet traffic would be in the form of videos by 2022. The computer vision community has embraced this challenge by offering the first building blocks to translate the visual data in segmented video clips into semantic tags. However, users usually require to go beyond tagging at the video level. For example, someone may want
Efficient Localization of Human Actions and Moments in Videos Victor Escorcia, Ph.D., Electrical and Computer Engineering Jun 11, 15:00 - 16:00 B3 L5 R5220 Computer Vision machine learning artificial intelligence Abstract We are stumbling across a video tsunami flooding our communication channels. The ubiquity of digital cameras and social networks has increased the amount of visual media content generated and shared by people, in particular videos. Cisco reports that 82% of the internet traffic would be in the form of videos by 2022. The computer vision community has embraced this challenge by offering the first building blocks to translate the visual data in segmented video clips into semantic tags. However, users usually require to go beyond tagging at the video level. For example, someone may want
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