We evaluate multiple architectures for the defense module, mainly GANs, an autoencoder, and a one-hidden-layer network. We effectively extract and prioritize SFs, thereby enhancing the model’s ability ...

Variational autoencoder (VAE) is widely used as a data enhancement technique. However, it faces challenges with inaccurate potential spatial distribution and poor reconstruction quality when dealing ...

Create an LSTM-based Autoencoder model to learn a representation of these signals. Detect anomalous segments (potentially high-stress signals) by computing reconstruction errors. Note on Training ...

In this paper, we propose a novel Transformer based approach, namely Cross-modal Contrastive Masked AutoEncoder (C2MAE), to Self-Supervised Learning (SSL) on compressed videos. A unified Transformer ...