InfoBayAI/Storyline_Verticle_Videos

Dataset Description

This dataset is a large-scale collection of storyline-based vertical video data, containing 2,279 hours of content, designed to support the development and training of advanced video understanding models, multimodal AI systems, and next-generation vision-language applications.

It consists of real-world vertical videos with narrative and storytelling structures commonly found in modern short-form platforms. The dataset captures diverse scene transitions, human interactions, contextual storytelling, and temporal progression, making it highly valuable for learning structured video comprehension and sequential reasoning.

This dataset is suitable for building scalable and production-ready AI systems for video understanding, video classification, video captioning, temporal reasoning, multimodal learning, and video retrieval tasks. It also supports training pipelines for Supervised Fine-Tuning (SFT), Self-Supervised Learning (SSL), Reinforcement Learning with Human Feedback (RLHF), and Video-Language Model (VLM) development.

Video Refining Process To ensure enterprise-grade quality and usability, the dataset undergoes a comprehensive 8-step video refining and processing pipeline before final delivery:

1. Duplicate Asset Elimination — Removal of duplicate or repeated video assets to maintain dataset uniqueness, consistency, and high-quality training data.
2. Vertical Format Validation — Verification that all video content meets vertical format compliance standards for mobile-first AI training requirements.
3. AV1 Codec Audit — Standardization of video codec to H.264 to ensure broad compatibility and consistent playback across platforms and models.
4. Intelligent Text Recognition — Automated ITR processing to detect, extract, and handle on-screen text within video frames for cleaner training data.
5. Animated Content Classification — Type tagging and classification of animated vs. real-world content to enable accurate dataset segmentation.
6. AI-Synthetic Media Detection — Authenticity filtering to identify and flag AI-generated or synthetic video content, ensuring real-world data integrity.
7. Brand Logo Intelligence — BLI detection to identify, track, and manage brand logos within video frames for compliance and neutrality.
8. Watermark Integrity Analysis — Detection and removal of watermarks to deliver clean, unobstructed video output ready for AI model training.

This processing pipeline ensures that the dataset is clean, scalable, production-ready, and optimized for video AI, computer vision, multimodal AI, SFT, and RLHF workflows.

Dataset Specification

Duration: 2.2k+ Hours
Modality: Video (Audio + Visual)
Format: Vertical 
Type: Storyline 

Key Use Cases

Short-form video understanding
Storyline and scene transition analysis
Video captioning and summarization
Multimodal recommendation systems
Speech-to-text and subtitle generation

Value of This Dataset

Enables advanced AI training for short-form vertical video platforms
Improves multimodal understanding of storytelling and scene dynamics
Supports AI systems for captioning, summarization, and recommendation
Helps build intelligent creator tools and automated editing systems
Enhances performance in video-language and multimodal reasoning tasks

Basic Json Schema

{
  "file_name": "string",
  "format": "string",
  "duration_seconds": "float",
  "width": "int32",
  "height": "int32",
  "fps": "float",
  "video_codec": "string",
  "audio_codec": "string",
  "bitrate": "int64",
  "file_size_bytes": "int64"
}

Data Creation

Procured through formal agreements and generated in the ordinary course of business.

Considerations

This dataset is provided for research and educational purposes only. It contains only sample data. For access to the full dataset and enterprise licensing options, please visit our website InfoBay.AI or contact us directly.

-Ph: (91) 8303174762
-Email: datareq@infobay.ai