Research map / Video / Video-language understanding
Collaborative Summarization of Topic-Related Videos
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 |
|---|---|---|---|
| Use collaborative sparse summarization with topic-related video context | CVS · CoSum | top-5 AP: 0.602 -> 0.687 | Helped |
| Use collaborative sparse summarization with topic-related video context | CVS · TVSum50 | top-5 AP: 0.345 -> 0.372 | Helped |
| Use CVS for collection-level concept visualization | multi-video summaries · CoSum | expert rating: 7.53 -> 8.20 | Helped |
| Use CVS for collection-level concept visualization | multi-video summaries · TVSum50 | expert rating: 5.70 -> 6.36 | Helped |
| Add topic-related neighborhood information (ablation) | CVS · CoSum | top-5 AP: 0.538 -> 0.687 | Helped |
| Add the diversity constraint (ablation) | CVS · CoSum | top-5 AP: 0.654 -> 0.687 | Helped |
| Use C3D rather than VGG features (ablation) | CVS · CoSum | top-5 AP: 0.643 -> 0.687 | Helped |
| Use C3D rather than shallow features (ablation) | CVS · CoSum | top-5 AP: 0.618 -> 0.687 | Helped |
Closest papers by meaning
- Video Summarization with Large Language Models (CVPR 2025 · similarity 0.87)
- Mitigating Semantic Collapse in Partially Relevant Video Retrieval (NeurIPS 2025 · similarity 0.85)
- Bridging Information Asymmetry in Text-video Retrieval: A Data-centric Approach (ICLR 2025 · similarity 0.85)
- V2Xum-LLM: Cross-Modal Video Summarization with Temporal Prompt Instruction Tuning (AAAI 2025 · similarity 0.84)
- Video Summarization Using Denoising Diffusion Probabilistic Model (AAAI 2025 · similarity 0.84)
- Watch Video, Catch Keyword: Context-aware Keyword Attention for Moment Retrieval and Highlight Detection (AAAI 2025 · similarity 0.84)
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.