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README.md
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license: cc-by-sa-4.0
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license: cc-by-sa-4.0
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---
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# recammaster_based_multi_camera_video_dataset
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**A Real-World Multi-Camera Video Dataset for Generative Vision AI**
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## 📌 Overview
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The MultiScene360 Dataset is designed to advance generative vision AI by providing synchronized multi-camera footage from real-world environments.
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💡 **Key Applications**:
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✔ Video generation & view synthesis
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✔ 3D reconstruction & neural rendering
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✔ Digital human animation systems
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✔ Virtual/augmented reality development
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## 📊 Dataset Specifications (Public Version)
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| Category | Specification |
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|---------------------|----------------------------------------|
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| Scenes | 10 base + 3 extended scenes |
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| Scene Duration | 10-20 seconds each |
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| Camera Views | 4 synchronized angles per scene |
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| Total Video Clips | ~144 |
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| Data Volume | 20-30GB (1080p@30fps) |
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*Commercial version available with 200+ scenes and 6-8 camera angles*
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## 🌆 Complete Scene Specification
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| ID | Environment | Location | Primary Action | Special Features |
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|------|-------------|-----------------|----------------------------|---------------------------|
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| S001 | Indoor | Living Room | Walk → Sit | Occlusion handling |
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| S002 | Indoor | Kitchen | Pour water + Open cabinet | Fine hand motions |
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| S003 | Indoor | Corridor | Walk → Turn | Depth perception |
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| S004 | Indoor | Desk | Type → Head turn | Upper body motions |
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| S005 | Outdoor | Park | Walk → Sit (bench) | Natural lighting |
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| S006 | Outdoor | Street | Walk → Stop → Phone check | Gait variation |
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| S007 | Outdoor | Staircase | Ascend stairs | Vertical movement |
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| S008 | Indoor | Corridor | Two people passing | Multi-person occlusion |
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| S009 | Indoor | Mirror | Dressing + mirror view | Reflection surfaces |
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| S010 | Indoor | Empty room | Dance movements | Full-body dynamics |
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| S011 | Indoor | Window | Phone call + clothes adjust| Silhouette + semi-reflections |
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| S012 | Outdoor | Shopping street | Walking + window browsing | Transparent surfaces + crowd |
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| S013 | Indoor | Night corridor | Walking + light switching | Low-light adaptation |
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## 🎥 Camera Configuration
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**Physical Setup**:
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cam01──────cam02
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\ /
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Subject
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/ \
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cam04──────cam03
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**Technical Details**:
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- **Cameras**: DJI Osmo Action 5 Pro (4 identical units)
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- **Mounting**: Tripod-stabilized at ~1.5m height
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- **Distance**: 2-3m from subject center
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- **FOV Overlap**: 20-30% between adjacent cameras
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## 🔍 Suggested Research Directions
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1. Cross-view consistency learning
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2. Novel view synthesis from sparse inputs
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3. Dynamic scene reconstruction
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4. Human motion transfer between viewpoints
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## 🚀 Access Information
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🎯 **FULL Dataset Download Here**: https://madacode.file.core.windows.net/root/360/MultiScene360%20Dataset.zip?sv=2023-01-03&st=2025-05-06T09%3A23%3A15Z&se=2028-01-07T09%3A23%3A00Z&sr=f&sp=r&sig=KnyHrAfeeCIpufeALFYRDAWDZ7W1F7hGUDToA26y9HQ%3D
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💼 **Commercial Inquiries**: contact@maadaa.ai
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**Usage Rights**:
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✔ Free for academic/commercial use
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✔ License: Attribution-NonCommercial-ShareAlike 4.0 International
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## About maadaa.ai
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Founded in 2015, maadaa.ai is a pioneering AI data service provider specializing in multimodal data solutions for generative AI development. We deliver end-to-end data services covering text, voice, image, and video datatypes – the core fuel for training and refining generative models.
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**Our Generative AI Data Solution includes:**
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ꔷ High-quality dataset collection & annotation tailored for LLMs and diffusion models
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ꔷ Scenario-based human feedback (RLHF/RLAIF) to enhance model alignment
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ꔷ One-stop data management through our MaidX platform for streamlined model training
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**Why Choose Us**:
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✓ Reduce real-world data collection costs by 70%+
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✓ Generate perfectly labeled training data at scale
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✓ API-first integration for synthetic pipelines
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*Empowering the next generation of interactive media and spatial computing**
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