What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Computer vision
- Programming language
Maneesh Agrawala focuses on Artificial intelligence, Computer vision, Computer graphics, Human–computer interaction and Visualization.
Maneesh Agrawala interconnects Digital photography and Polygon in the investigation of issues within Computer vision.
His studies deal with areas such as Video tracking, Set, Interface and Compositing as well as Computer graphics.
Maneesh Agrawala usually deals with Set and limits it to topics linked to Interface and Undo, Poisson image editing and Pixel.
His Human–computer interaction research incorporates themes from User interface, Multimedia, Information visualization and Data visualization.
His Visualization research also works with subjects such as
- Information extraction that intertwine with fields like Bitmap and Contextual image classification,
- Data mining most often made with reference to Information retrieval.
His most cited work include:
- Interactive digital photomontage (957 citations)
- Digital photography with flash and no-flash image pairs (926 citations)
- Interactive video cutout (353 citations)
What are the main themes of his work throughout his whole career to date?
Maneesh Agrawala mainly focuses on Artificial intelligence, Computer vision, Computer graphics, Human–computer interaction and Visualization.
His Artificial intelligence research is multidisciplinary, incorporating elements of Machine learning and Natural language processing.
He combines subjects such as Image, Interface and Set with his study of Computer graphics.
His biological study spans a wide range of topics, including Process, Interface and Engineering drawing.
The various areas that Maneesh Agrawala examines in his Human–computer interaction study include User interface, Multimedia, Information visualization and Gesture.
His work carried out in the field of Visualization brings together such families of science as World Wide Web and Information retrieval.
He most often published in these fields:
- Artificial intelligence (31.54%)
- Computer vision (24.48%)
- Computer graphics (23.65%)
What were the highlights of his more recent work (between 2015-2021)?
- Human–computer interaction (22.41%)
- Artificial intelligence (31.54%)
- Information retrieval (6.64%)
In recent papers he was focusing on the following fields of study:
Maneesh Agrawala mainly focuses on Human–computer interaction, Artificial intelligence, Information retrieval, Speech recognition and World Wide Web.
His research integrates issues of Video editing, Gesture, Gaze and Graphics in his study of Human–computer interaction.
The concepts of his Artificial intelligence study are interwoven with issues in Computer vision and Natural language processing.
His study in the field of Image texture, Panorama and Stereoscopy also crosses realms of Reflection mapping.
His study in Information retrieval is interdisciplinary in nature, drawing from both Object, Information visualization and Set.
In his work, Video tracking and Video based is strongly intertwined with Multimedia, which is a subfield of World Wide Web.
Between 2015 and 2021, his most popular works were:
- Saliency in VR: How Do People Explore Virtual Environments? (149 citations)
- Text-based editing of talking-head video (68 citations)
- State of the Art on Neural Rendering (54 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Programming language
- Computer vision
Maneesh Agrawala mainly investigates Human–computer interaction, Artificial intelligence, Graphics, Video editing and Multimedia.
His Human–computer interaction research includes elements of Voice user interface, Interface, Control, Direct voice input and Task.
His Artificial intelligence research includes elements of Computer vision and Natural language processing.
His Computer vision research is multidisciplinary, incorporating perspectives in Immersion, Visual attention and Salience.
His Graphics research integrates issues from Speech recognition, Expression and Face.
His Multimedia study integrates concerns from other disciplines, such as Software deployment, Online community and Creative work.
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