R3D residual network

R3D (Residual 3D) network is a type of 3D convolutional neural network (CNN) architecture that is designed for video classification tasks. It builds upon the idea of residual connections in the ResNet architecture to improve the training and performance of 3D CNNs.

In the R3D architecture, residual connections are added between convolutional layers, which allows the network to learn the residual information between feature maps and avoid the vanishing gradient problem. Additionally, the R3D network uses 3D convolutional filters to capture spatiotemporal features in videos, allowing it to better model the motion information in video frames.

R3D networks have been used successfully in various video classification tasks, such as action recognition, gesture recognition, and video captioning.