Search Results for "3d capture"

Kinetics-I3D, developed by Google DeepMind, provides trained models and implementation code for the Inflated 3D ConvNet (I3D) architecture introduced in the paper “Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset” (CVPR 2017). The I3D model extends the 2D convolutional structure of Inception-v1 into 3D, allowing it to capture spatial and temporal information from videos for action recognition. This repository includes pretrained I3D models on the Kinetics dataset, with both RGB and optical flow input streams. ...

...Harvey and was developed with support from the U.S. DOE, Ballard, and Queen's University. Derivative works of FAST-FC include FC-APOLLO which is a forked branch of this project intended to capture the code state at the exit of the funded DOE project. FAST-FC is the open and active community branch. FAST-FC is developed and maintained by the original creator and developer, David B. Harvey. Features of FAST-fc include transport of gases and liquids, multi-step reaction kinetics, transient and steady state operation for performance and durability, and scalable dimensionality from 1D - 3D domains. ...