j-min / Adversarial_video_summary
Unofficial PyTorch Implementation of SUM-GAN from "Unsupervised Video Summarization with Adversarial LSTM Networks" (CVPR 2017)
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Adversarial_Video_Summary
PyTorch Implementation of SUM-GAN
- from "Unsupervised Video Summarization with Adversarial LSTM Networks (CVPR 2017)"
- by Behrooz Mahasseni, Michael Lam and Sinisa Todorovic
- Code Author: Jaemin Cho
- Used as baseline for unsupervised video summarization
Changes from Original paper
- Video feature extractor
- GoogleNet pool5 (1024) => ResNet-101 pool5 (2048)
- Followed by linear projection to 500-dim
- Stable GAN Training
- Discriminator's learning rate: 1e-5 (Others: 1e-4)
- Fix Discriminators' parameters for first 15 steps at every epoch.
Model figures
Algorithm
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