His primary areas of study are Artificial intelligence, Computer vision, Pattern recognition, Object detection and Object. His work in Artificial intelligence is not limited to one particular discipline; it also encompasses Machine learning. His study in the field of Cognitive neuroscience of visual object recognition, Articulated body pose estimation, Pose and Pixel is also linked to topics like Object-class detection.
His Cognitive neuroscience of visual object recognition study integrates concerns from other disciplines, such as Video tracking and Pattern recognition. The Pattern recognition study combines topics in areas such as Image and Data mining. His work deals with themes such as Image sensor, Feature, Image processing, Contextual image classification and Supervised learning, which intersect with Object detection.
His primary scientific interests are in Artificial intelligence, Computer vision, Object, Pattern recognition and Segmentation. His Machine learning research extends to Artificial intelligence, which is thematically connected. His work carried out in the field of Computer vision brings together such families of science as Detector and Pattern recognition.
The concepts of his Object study are interwoven with issues in Motion, Representation and Automatic image annotation. His biological study spans a wide range of topics, including Pixel and Algorithm. His studies in Object detection integrate themes in fields like Contextual image classification, Support vector machine and Image processing.
Artificial intelligence, Object, Computer vision, Segmentation and Image are his primary areas of study. His research integrates issues of Natural language processing, Machine learning and Pattern recognition in his study of Artificial intelligence. His Pattern recognition research is multidisciplinary, relying on both Domain, Adaptation and Test set.
His work in Object covers topics such as Pattern recognition which are related to areas like Human–computer interaction. Vittorio Ferrari works mostly in the field of Computer vision, limiting it down to concerns involving Representation and, occasionally, CAD. His Segmentation study combines topics in areas such as Pixel, Algorithm and Automatic image annotation.
His scientific interests lie mostly in Artificial intelligence, Object, Segmentation, Image and Pattern recognition. His research in Artificial intelligence intersects with topics in Machine learning and Computer vision. His study on Voxel, Automatic image annotation and Image segmentation is often connected to Focus and Space as part of broader study in Computer vision.
His Object study frequently intersects with other fields, such as Pattern recognition. In his work, Closed captioning and Word is strongly intertwined with Natural language processing, which is a subfield of Image. His research investigates the connection with Pattern recognition and areas like Representation which intersect with concerns in Pixel, Bilinear interpolation, Machine vision and Upsampling.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
Measuring the Objectness of Image Windows
B. Alexe;T. Deselaers;V. Ferrari.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2012)
What is an object
Bogdan Alexe;Thomas Deselaers;Vittorio Ferrari.
computer vision and pattern recognition (2010)
ClassCut for unsupervised class segmentation
Bogdan Alexe;Thomas Deselaers;Vittorio Ferrari.
european conference on computer vision (2010)
Progressive search space reduction for human pose estimation
V. Ferrari;M. Marin-Jimenez;A. Zisserman.
computer vision and pattern recognition (2008)
Groups of Adjacent Contour Segments for Object Detection
V. Ferrari;L. Fevrier;F. Jurie;C. Schmid.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2008)
Fast Object Segmentation in Unconstrained Video
Anestis Papazoglou;Vittorio Ferrari.
international conference on computer vision (2013)
Segmentation propagation in imagenet
Daniel Kuettel;Matthieu Guillaumin;Vittorio Ferrari.
european conference on computer vision (2012)
Object detection by contour segment networks
Vittorio Ferrari;Tinne Tuytelaars;Luc Van Gool.
european conference on computer vision (2006)
What’s the Point: Semantic Segmentation with Point Supervision
Amy L. Bearman;Olga Russakovsky;Vittorio Ferrari;Li Fei-Fei.
european conference on computer vision (2016)
Learning Visual Attributes
Vittorio Ferrari;Andrew Zisserman.
neural information processing systems (2007)
If you think any of the details on this page are incorrect, let us know.
We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below: