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The dataset is labeled with semantic labels for 32 semantic classes. over 700 images Images Object recognition and classification 2008 [56] [57] [58] Gabriel J. Brostow, Jamie Shotton, Julien Fauqueur, Roberto Cipolla RailSem19 RailSem19 is a dataset for understanding scenes for vision systems on railways. The dataset is labeled semanticly and ...
A neural radiance field (NeRF) is a method based on deep learning for reconstructing a three-dimensional representation of a scene from two-dimensional images. The NeRF model enables downstream applications of novel view synthesis, scene geometry reconstruction, and obtaining the reflectance properties of the scene. Additional scene properties ...
A facial expression database is a collection of images or video clips with facial expressions of a range of emotions.Well-annotated (emotion-tagged) media content of facial behavior is essential for training, testing, and validation of algorithms for the development of expression recognition systems.
The datasets are classified, based on the licenses, as Open data and Non-Open data. The datasets from various governmental-bodies are presented in List of open government data sites. The datasets are ported on open data portals. They are made available for searching, depositing and accessing through interfaces like Open API. The datasets are ...
Caltech 101 is a data set of digital images created in September 2003 and compiled by Fei-Fei Li, Marco Andreetto, Marc 'Aurelio Ranzato and Pietro Perona at the California Institute of Technology.
Xiaoming Liu is a Chinese-American computer scientist and an academic.He is a Professor in the Department of Computer Science and Engineering, MSU Foundation Professor as well as Anil K. and Nandita Jain Endowed Professor of Engineering at Michigan State University.
For 25 years and counting, John McNaughton's sweaty Florida-set thriller, Wild Things, has kept viewers hot and bothered with its blend of steamy sex scenes and crazy plot twists.But in a new ...
The text in scene images varies in shape, font, colour and position. The recognition of scene text is further complicated sometimes by non-uniform illumination and focus. To improve scene text recognition, the International Conference on Document Analysis and Recognition (ICDAR) conducts a robust reading competition once in two years.