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Found 6 papers, 0 papers with code
SlideNet: Fast and Accurate Slide Quality Assessment Based on Deep Neural Networks
In order to address the quality assessment problem, we propose a deep neural network based framework to automatically assess the slide quality in a semantic way.
Towards Miss Universe Automatic Prediction: The Evening Gown Competition
Can we predict the winner of Miss Universe after watching how they stride down the catwalk during the evening gown competition?
Joint Recognition and Segmentation of Actions via Probabilistic Integration of Spatio-Temporal Fisher Vectors
The final classification decision for each frame is then obtained by integrating the class probabilities at the frame level, which exploits the overlapping of the temporal windows.
Comparative Evaluation of Action Recognition Methods via Riemannian Manifolds, Fisher Vectors and GMMs: Ideal and Challenging Conditions
We evaluate these action recognition techniques under ideal conditions, as well as their sensitivity in more challenging conditions (variations in scale and translation).
Multi-Action Recognition via Stochastic Modelling of Optical Flow and Gradients
In this paper we propose a novel approach to multi-action recognition that performs joint segmentation and classification.
Summarisation of Short-Term and Long-Term Videos using Texture and Colour
We present a novel approach to video summarisation that makes use of a Bag-of-visual-Textures (BoT) approach.
