Tran, "Facial Expression Recognition Using Residual Masking Network", IEEE 25th International Conference on Pattern Recognition, 2020, 4513-4519. I will try to address everything as soon as possible. That being said, thanks to everyone for your continued help and feedback as it is really appreciated. Note: Unfortunately, I am currently join a full-time job and research on another topic, so I'll do my best to keep things up to date, but no guarantees. GradCAM visualization and Pooling method for visualize activations.Imagenet trained and pretrained weights.We have accumulated the following to-do list, which we hope to complete in the near future Presentation slide PDF (in English) with full appendix. Run gen_ensemble.py file to generate accuracy for example methods.Edit file gen_results and run it to generate result offline for each model.Link to download can be found on Benchmarking section. Download all needed trained weights and located on.I used no-weighted sum avarage ensemble method to fusing 7 different models together, to reproduce results, you need to do some steps: (Read this article for more information, there will be some bugs if you blindly run the code without reading). main_imagenet.py -a resnet34 -dist-url 'tcp://127.0.0.1:12345' -dist-backend 'nccl' -multiprocessing-distributed -world-size 1 -rank 0įor student, who takes care of font family of confusion matrix and would like to write things in LaTeX, below is an example for generating a striking confusion matrix. To perform training resnet34 on 4 V100 GPUs on a single machine: python.
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