3 accepted papers
This paper introduces a novel framework named the Ranking Auxiliary Classifier Generative Adversarial Network (RAC-GAN), which leverages a dual strategy involving a Generative Adversarial Network (GAN)-based data generator for oversampling and a Reinforcement Learning (RL)-based ranker for undersamp…
We propose a novel concept of Deep Part Embeddings (DPEs), which can be used to learn new Convolutional Neural Networks (CNNs) for different classes. We define DPE as a neuron of a trained CNN along with its network of filter activations that is interpretable as a part of a class that the neuron con…
In this paper, we propose the Radial Loss which utilizes category and sub-category labels to learn an order-preserving fine-grained video similarity metric. We propose an end-to-end quadlet-based Convolutional Neural Network (CNN) combined with Long Short-term Memory (LSTM) Unit to model video simil…