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Found 5 papers, 1 papers with code
Using Decoupled Features for Photo-realistic Style Transfer
In this work we propose a photorealistic style transfer method for image and video that is based on vision science principles and on a recent mathematical formulation for the deterministic decoupling of sample statistics.
Learning Football Body-Orientation as a Matter of Classification
Orientation is a crucial skill for football players that becomes a differential factor in a large set of events, especially the ones involving passes.
Using Player's Body-Orientation to Model Pass Feasibility in Soccer
Given a monocular video of a soccer match, this paper presents a computational model to estimate the most feasible pass at any given time.
Always Look on the Bright Side of the Field: Merging Pose and Contextual Data to Estimate Orientation of Soccer Players
Although orientation has proven to be a key skill of soccer players in order to succeed in a broad spectrum of plays, body orientation is a yet-little-explored area in sports analytics' research.
Convolutional Neural Networks Deceived by Visual Illusions
In particular, we show that CNNs trained for image denoising, image deblurring, and computational color constancy are able to replicate the human response to visual illusions, and that the extent of this replication varies with respect to variation in architecture and spatial pattern size.
