Search Results for author:
Found 5 papers, 3 papers with code
Latent Bernoulli Autoencoder
In this work, we pose a question whether it is possible to design and train an autoencoder model in an end-to-end fashion to learn latent representations in multivariate Bernoulli space, and achieve performance comparable with the current state-of-the-art variational methods.
Iterative Self-Learning: Semi-Supervised Improvement to Dataset Volumes and Model Accuracy
A novel semi-supervised learning technique is introduced based on a simple iterative learning cycle together with learned thresholding techniques and an ensemble decision support system.
A Comparison of Embedded Deep Learning Methods for Person Detection
Recent advancements in parallel computing, GPU technology and deep learning provide a new platform for complex image processing tasks such as person detection to flourish.
Summarizing Videos with Attention
In this work we propose a novel method for supervised, keyshots based video summarization by applying a conceptually simple and computationally efficient soft, self-attention mechanism.
Ranked #3 on
Video Summarization
on TvSum
(using extra training data)
AMNet: Memorability Estimation with Attention
Further on we study the impact of the attention mechanism on the memorability estimation and evaluate our network on the SUN Memorability and the LaMem datasets.
