Generalized Zero-Shot Learning using Multimodal Variational Auto-Encoder with Semantic Concepts

no code implementations • 26 Jun 2021 • Nihar Bendre, Kevin Desai, Peyman Najafirad

To overcome this problem, we propose a Multimodal Variational Auto-Encoder (M-VAE) which can learn the shared latent space of image features and the semantic space.

Few-Shot Learning Generalized Zero-Shot Learning

Show Why the Answer is Correct! Towards Explainable AI using Compositional Temporal Attention

no code implementations • 15 May 2021 • Nihar Bendre, Kevin Desai, Peyman Najafirad

This results in achieving better understanding of complex questions and also provides reasoning as to why the module predicts a particular answer.

Question Answering Visual Question Answering

Learning from Few Samples: A Survey

no code implementations • 30 Jul 2020 • Nihar Bendre, Hugo Terashima Marín, Peyman Najafirad

Deep neural networks have been able to outperform humans in some cases like image recognition and image classification.

Data Augmentation Few-Shot Learning +1

Human Action Performance using Deep Neuro-Fuzzy Recurrent Attention Model

no code implementations • 29 Jan 2020 • Nihar Bendre, Nima Ebadi, John J. Prevost, Paul Rad

A great number of computer vision publications have focused on distinguishing between human action recognition and classification rather than the intensity of actions performed.

Action Recognition Temporal Action Localization