# Survey of Dense Video Captioning: Techniques, Resources, and Future Perspectives
## 4 Datasets for Dense Video Captioning
### Detailed Descriptions
Annotations for MSR-VTT are provided by 1327 AMT workers, ensuring each video clip is accompanied by multiple captions that offer comprehensive coverage of various aspects of the video content, enhancing the understanding of video semantics. MSR-VTT comprises 10,000 video clips sourced from 7180 videos, with an average of 20 captions per video. 6. Charades Charades Charades is a large-scale video dataset designed for activity understanding and video description tasks [53]. It contains videos of people performing daily activities in various indoor scenes. The annotations for Charades include action labels, temporal intervals, and natural language descriptions, collected through Amazon Mechanical Turk to provide comprehensive coverage of video content. Charades comprises 9848 videos, recorded by 267 people in 15 different indoor scenes. Each video is annotated with multiple action classes and descriptions. 7. VTW VTG Video Titles in the Wild) is a large-scale dataset of user-generated videos automatically crawled from online communities [54]. It contains 18,100 videos with an average duration of 1.5 min, each associated with a concise title produced by an editor. Each video is annotated with a single title sentence describing the most salient event, accompanied by 1-3 longer description sentences. Highlight moments corresponding to the titles are manually labeled in a subset. The dataset spans 213.2 h in total, making it a challenging benchmark for video title generation tasks. 8. ActivityNet Captions ActivityNet Captions [2] is a large-scale dataset for dense video captioning, featuring over 20,000 videos segmented into multiple temporal intervals. With 100K descriptions totaling 849 h, each averaging 13.48 words and capturing 36 s of video content, it comprehensively annotates activities within each interval. Annotations in the dataset include multiple temporally localized sentences per video, averaging 3.65 per clip, which collectively cover 94.6% of video content with 10% overlap, ideal for studying concurrent events. Covering over 849 video hours, the dataset encompasses 20K videos and generates 100\(k\) sentences. Both sentence length and count per video follow normal distributions, indicative of varying video durations. 9. YouCook2 YouCook2 YouCook2 [4] is a comprehensive cooking video dataset, featuring 2000 YouTube videos across 89 recipes from diverse cuisines. It covers a wide range of cooking styles, ingredients, and utensils, primarily used for video summarization, recipe generation, and dense video captioning tasks. YouCook2 includes temporal boundaries of cooking steps and ingredients, along with textual descriptions for each step. These annotations provide detailed, step-by-step insights into the cooking process. Comprising 2000 cooking videos, YouCook2 offers a substantial dataset for research and development in cooking-related video analysis. 10. BDD-X The BDD-X [55] dataset is a large-scale video dataset designed for explaining self-driving vehicle behaviors. It contains over 77 h of driving videos with human-annotated descriptions and explanations of vehicle actions. Each video clip is annotated with action descriptions and justifications. Annotators view the videos from a driving instructor's perspective, describing what the driver is doing and why. The dataset comprises 6984 videos, split into training (5588), validation (698), and test sets (698). Over 26,000 actions are annotated across 8.4 million frames. 11. VideoStory VideoStory [56] is a novel dataset tailored for multi-sentence video description. It comprises 20\(k\) videos sourced from social media, spanning diverse topics and engaging narratives. Each video is annotated with multiple paragraphs, containing 123\(k\) sentences temporally aligned to video segments. On average, each video has 4.67 annotated sentences. The dataset encompasses 396 h of video content, divided into training (17,098 videos), validation (999 videos), test (1011 videos), and blind test sets (1039 videos). 12.