1. Duration

Monday, December 12th, 2022 - Saturday, December 17th, 2022

2. Learning Record

2.1 Added CBAM

I added cbam [1] on the SOFTNet, but it ran as shit. I tried some fine-tuning, but I still got terrible results.

2.2 Refactored tf.dataset

I tried to use the generator to generate data for the vision transformer model, but the yield would yield a tensor in the shape of [none, none, none, none] which causes errors.

2.3 Request for the Test Dataset

I sent the request e-mail and got the reply with the link to the dataset within one morning, the morning of December 15th, 2022.

The efficiency shocked me a lot!

2.4 Deploy on New Server

The training made the Windows server really slow even stuck. Consequently, I got a new account for the Linux server. It has two GTX 2080 Ti GPUs, cool!

2.5 Paper Reading

I read the paper [2]. It uses traditional methods but got the first prize in the competition. Unbelievable!

3. Feelings

3.1 Busy

The code runs as shit and I needed to learn how to use Linux.

References

[1]S. Woo, J. Park, J.-Y. Lee, and I. S. Kweon, “CBAM: Convolutional Block Attention Module,” in Computer Vision – ECCV 2018, Cham, 2018, pp. 3–19.

[2]J. Yu, Z. Cai, Z. Liu, G. Xie, and P. He, “Facial Expression Spotting Based on Optical Flow Features,” in Proceedings of the 30th ACM International Conference on Multimedia, New York, NY, USA, 2022, pp. 7205–7209. doi: 10.1145/3503161.3551608.