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Supervised Video Summarization

Supervised video summarization rely on datasets with human-labeled ground-truth annotations (either in the form of video summaries, as in the case of the SumMe dataset, or in the form of frame-level importance scores, as in the case of the TVSum dataset), based on which they try to discover the underlying criterion for video frame/fragment selection and video summarization.

Source: Video Summarization Using Deep Neural Networks: A Survey

Papers

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Showing 1–25 of 28 papers

TitleStatusHype
TRIM: A Self-Supervised Video Summarization Framework Maximizing Temporal Relative Information and Representativeness—0
FullTransNet: Full Transformer with Local-Global Attention for Video Summarization—0
CSTA: CNN-based Spatiotemporal Attention for Video SummarizationCode0
Language-Guided Self-Supervised Video Summarization Using Text Semantic Matching Considering the Diversity of the Video—0
Align and Attend: Multimodal Summarization with Dual Contrastive LossesCode1
Relational Reasoning Over Spatial-Temporal Graphs for Video Summarization—0
Progressive Video Summarization via Multimodal Self-supervised LearningCode1
Joint Video Summarization and Moment Localization by Cross-Task Sample Transfer—0
Video Joint Modelling Based on Hierarchical Transformer for Co-summarizationCode1
Combining Global and Local Attention with Positional Encoding for Video SummarizationCode1
A Stacking Ensemble Approach for Supervised Video Summarization—0
Hierarchical Multimodal Transformer to Summarize Videos—0
Use of Affective Visual Information for Summarization of Human-Centric Videos—0
CLIP-It! Language-Guided Video SummarizationCode0
Self-Attention Recurrent Summarization Network with Reinforcement Learning for Video Summarization TaskCode1
Supervised Video Summarization via Multiple Feature Sets with Parallel AttentionCode1
How Good is a Video Summary? A New Benchmarking Dataset and Evaluation Framework Towards Realistic Video Summarization—0
DSNet: A Flexible Detect-to-Summarize Network for Video SummarizationCode1
Query Twice: Dual Mixture Attention Meta Learning for Video Summarization—0
Weakly Supervised Video Summarization by Hierarchical Reinforcement Learning—0
Test-Time Training with Self-Supervision for Generalization under Distribution ShiftsCode0
Discriminative Feature Learning for Unsupervised Video SummarizationCode0
Weakly-supervised Video Summarization using Variational Encoder-Decoder and Web PriorCode0
Improving Sequential Determinantal Point Processes for Supervised Video Summarization—0
How Local is the Local Diversity? Reinforcing Sequential Determinantal Point Processes with Dynamic Ground Sets for Supervised Video Summarization—0
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