Research map / Video / Video segmentation and tracking
Unsupervised Video Summarization With Adversarial LSTM Networks
Check your idea against 108,967 papers
AI-extracted summary. Written by AI from the paper's title only (no summary yet). Numbers and claims can be wrong or missing context, so check the paper before you cite or build on it.
Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Add GAN loss to decoder training (ablation) | SUM-GAN · SumMe | F-score: 34.6 -> 38.7 | Helped |
| Add GAN loss to decoder training (ablation) | SUM-GAN · TVSum | F-score: 49.5 -> 50.8 | Helped |
| Add GAN loss to decoder training (ablation) | SUM-GAN · OpenVideo | F-score: 69.3 -> 71.5 | Helped |
| Add GAN loss to decoder training (ablation) | SUM-GAN · YouTube | F-score: 56.9 -> 58.9 | Helped |
| Add DPP diversity regularization instead of summary-length regularization (ablation) | SUM-GAN · SumMe, TVSum, OpenVideo, YouTube | F-score: 38.7 -> 39.1; 50.8 -> 51.7; 71.5 -> 72.8; 58.9 -> 60.1 | Mixed |
| Add repelling diversity regularization instead of summary-length regularization (ablation) | SUM-GAN · SumMe, TVSum, OpenVideo, YouTube | F-score: 38.7 -> 38.5; 50.8 -> 51.9; 71.5 -> 72.3; 58.9 -> 59.6 | Mixed |
| Add summary-length regularization (ablation) | SUM-GAN · SumMe, TVSum, OpenVideo, YouTube | F-score: 35.7 -> 38.7; 50.1 -> 50.8; 69.8 -> 71.5; 57.1 -> 58.9 | Helped |
| Add randomly sampled summaries to GAN training (ablation) | SUM-GAN · SumMe, TVSum, YouTube | F-score: 37.2 -> 38.7; 50.4 -> 50.8; 58.4 -> 58.9 | Helped |
| Add randomly sampled summaries to GAN training (ablation) | SUM-GAN · OpenVideo | F-score: 71.5 -> 71.5 | No clear effect |
| Use keyframe supervision (ablation) | SUM-GAN · SumMe, TVSum, OpenVideo, YouTube | F-score: 38.7 -> 41.7; 50.8 -> 56.3; 71.5 -> 77.3; 58.9 -> 62.5 | Helped |
Closest papers by meaning
- Cycle-SUM: Cycle-Consistent Adversarial LSTM Networks for Unsupervised Video Summarization (AAAI 2019 · similarity 0.94)
- Video Summarization by Learning From Unpaired Data (CVPR 2019 · similarity 0.90)
- Video Summarization Using Denoising Diffusion Probabilistic Model (AAAI 2025 · similarity 0.85)
- Video Summarization with Large Language Models (CVPR 2025 · similarity 0.85)
- Scaling Up Video Summarization Pretraining with Large Language Models (CVPR 2024 · similarity 0.85)
- V2Xum-LLM: Cross-Modal Video Summarization with Temporal Prompt Instruction Tuning (AAAI 2025 · similarity 0.85)
Writing a paper in this area? scime draft is a free LaTeX editor with AI included, real-time co-authors and a check of your references and venue rules before you submit. It also imports OpenAI Prism projects.
