Unsupervised Video Summarization On Summe

Metrics

F1-score

Parameters (M)

training time (s)

Results

Performance results of various models on this benchmark

				Paper Title
TAC-SUM	54.48	-	-	Cluster-based Video Summarization with Temporal Context Awareness
SegSum	54	5.25	-	Integrate the temporal scheme for unsupervised video summarization via attention mechanism
RS-SUM	52.0	-	-	Adopting Self-Supervised Learning into Unsupervised Video Summarization through Restorative Score.
CSNet	51.3	100.76	568.6	Discriminative Feature Learning for Unsupervised Video Summarization
CA-SUM	51.1	5.25	24	Summarizing Videos using Concentrated Attention and Considering the Uniqueness and Diversity of the Video Frames
AC-SUM-GAN	50.8	26.75	2825	AC-SUM-GAN: Connecting Actor-Critic and Generative Adversarial Networks for Unsupervised Video Summarization
SUM-GAN-AAE	48.9	24.31	1639	Unsupervised Video Summarization via Attention-Driven Adversarial Learning
SUM-GAN-sl	47.8	23.31	1185	A Stepwise, Label-based Approach for Improving the Adversarial Training in Unsupervised Video Summarization
Cycle-SUM	41.9	-	-	Cycle-SUM: Cycle-consistent Adversarial LSTM Networks for Unsupervised Video Summarization
DR-DSN	41.4	2.63	19.8	Deep Reinforcement Learning for Unsupervised Video Summarization with Diversity-Representativeness Reward

0 of 10 row(s) selected.

Unsupervised Video Summarization On Summe

Metrics

F1-score

Parameters (M)

training time (s)

Results

Performance results of various models on this benchmark

				Paper Title
TAC-SUM	54.48	-	-	Cluster-based Video Summarization with Temporal Context Awareness
SegSum	54	5.25	-	Integrate the temporal scheme for unsupervised video summarization via attention mechanism
RS-SUM	52.0	-	-	Adopting Self-Supervised Learning into Unsupervised Video Summarization through Restorative Score.
CSNet	51.3	100.76	568.6	Discriminative Feature Learning for Unsupervised Video Summarization
CA-SUM	51.1	5.25	24	Summarizing Videos using Concentrated Attention and Considering the Uniqueness and Diversity of the Video Frames
AC-SUM-GAN	50.8	26.75	2825	AC-SUM-GAN: Connecting Actor-Critic and Generative Adversarial Networks for Unsupervised Video Summarization
SUM-GAN-AAE	48.9	24.31	1639	Unsupervised Video Summarization via Attention-Driven Adversarial Learning
SUM-GAN-sl	47.8	23.31	1185	A Stepwise, Label-based Approach for Improving the Adversarial Training in Unsupervised Video Summarization
Cycle-SUM	41.9	-	-	Cycle-SUM: Cycle-consistent Adversarial LSTM Networks for Unsupervised Video Summarization
DR-DSN	41.4	2.63	19.8	Deep Reinforcement Learning for Unsupervised Video Summarization with Diversity-Representativeness Reward

0 of 10 row(s) selected.