GitHub - Sam-x-y-z/PBL-Project: Video Summarization project implemented using ResNeXt-101 with PyTorch's LSTM and an MLP for importance score prediction, Kernal Temporal Segmentation is applied along with Dynamic Programming KnapSack to maximize the importance of frames in the summary generation. The final visual is created using smoothly combining frames with the MoviePy module.

Sam-x-y-z / PBL-Project Public

forked from MrThetaIII/PBL-Project

Notifications You must be signed in to change notification settings
Fork 0
Star 0

Video Summarization project implemented using ResNeXt-101 with PyTorch's LSTM and an MLP for importance score prediction, Kernal Temporal Segmentation is applied along with Dynamic Programming KnapSack to maximize the importance of frames in the summary generation. The final visual is created using smoothly combining frames with the MoviePy module.

MIT license

0 stars 2 forks Branches Tags Activity

Star

Notifications

Branches Tags

Name		Name	Last commit message	Last commit date
Latest commit History 8 Commits
Demo		Demo
KTS+VideoSummery		KTS+VideoSummery
Training LSTM-MLP		Training LSTM-MLP
generate_result_video		generate_result_video
models		models
videos/tvsum		videos/tvsum
.gitignore		.gitignore
LICENSE		LICENSE
LSTM_Video_Summarization_utilizing_continuous_importance_scores_LSTM_VS_c.pdf		LSTM_Video_Summarization_utilizing_continuous_importance_scores_LSTM_VS_c.pdf
Prepare_dataset.py		Prepare_dataset.py
README.md		README.md
class_names_list		class_names_list
classify.py		classify.py
dataset.py		dataset.py
input		input
main.py		main.py
mean.py		mean.py
model.py		model.py
opts.py		opts.py
output_score.json		output_score.json
read_json.py		read_json.py
spatial_transforms.py		spatial_transforms.py
temporal_transforms.py		temporal_transforms.py
test.py		test.py
train.py		train.py
validation.py		validation.py
video-classification-3d-cnn-pytorch-master.rar		video-classification-3d-cnn-pytorch-master.rar