Paper in IJCNN (2017) on “Towards Using Visual Attributes to Infer Image Sentiment Of Social Events”
Paper Abstract Widespread and pervasive adoption of smartphones has led to the instant sharing of photographs that capture events ranging from mundane to life-altering happenings. We propose to capture sentiment information of such social event images leveraging their visual content. Our method extracts an intermediate visual representation of social event images based on the visual […]
Paper Abstract We propose to leverage concept-level representations for complex event recognition in photographs given limited training examples. We introduce a novel framework to discover event concept attributes from the web and use that to extract semantic features from images and classify them into social event categories with few training examples. Discovered concepts include a variety of objects, scenes, […]
Kudos to the team from Machine Perception at Google Research that just launched the Motion Still App to generate novel photos on an iOS device. This work is in part aimed at combining efforts like Video Textures and Video Stabilization and a lot more. Source: Research Blog: Motion Stills – Create beautiful GIFs from Live […]
Paper Abstract We present an approach for identifying picturesque highlights from large amounts of egocentric video data. Given a set of egocentric videos captured over the course of a vacation, our method analyzes the videos and looks for images that have good picturesque and artistic properties. We introduce novel techniques to automatically determine aesthetic features […]
Presentation at Max-Planck-Institut für Informatik in Saarbrücken (2015): "Video Analysis and Enhancement"
Video Analysis and Enhancement: Spatio-Temporal Methods for Extracting Content from Videos and Enhancing Video Output Irfan Essa (prof.irfanessa.com) Georgia Institute of Technology School of Interactive Computing Hosted by Max-Planck-Institut für Informatik in Saarbrucken (Bernt Schiele, Director of Computer Vision and Multimodal Computing) Abstract In this talk, I will start with describing the pervasiveness of image and video content, […]
Presentation at Max-Planck-Institute for Intelligent Systems in Tübingen (2015): "Data-Driven Methods for Video Analysis and Enhancement"
Irfan EssaGeorgia Institute of Technology Thursday, September 10, 2 pm,Max Planck House Lecture Hall (Spemannstr. 36)Hosted by Max-Planck-Institute for Intelligent Systems (Michael Black, Director of Perceiving Systems) Abstract In this talk, I will start with describing the pervasiveness of image and video content, and how such content is growing with the ubiquity of cameras. I will use […]