Supplementary for Project RISE: Recognizing Industrial Smoke Emissions

The supplementary materials contain model weights for the RGB-I3D and RGB-TC models for the following paper:Yen-Chia Hsu, Ting-Hao (Kenneth) Huang, Ting-Yao Hu, Paul Dille, Sean Prendi, Ryan Hoffman, Anastasia Tsuhlares, Jessica Pachuta, Randy Sargent, and Illah Nourbakhsh. 2021. Project RISE: Recognizing Industrial Smoke Emissions. Proceedings of the AAAI Conference on Artificial Intelligence (AAAI 2021).Check the following GitHub repository about how to use the model weights:https://github.com/CMU-CREATE-Lab/deep-smoke-machineTwo folders in this repository, RGB-I3D and RGB-TC, correspond to two models in the paper. Inside each model, there are splits from S0 to S5, corresponding to the train/validation/test splits in the paper. Inside each split, there are three folders: metadata, model, and viz. The metadata folder shows the videos that are used for each split. The model folder contains the best model weights in the experiment. The viz folder contains visualizations of true positive, false positive, true negative, and false negative examples.