--- license: other task_categories: - video-classification - image-classification - feature-extraction language: - en - zh tags: - multi-view - 4d-human - human-motion - pose-estimation - long-sequence - embodied-ai - pose_estimation - video pretty_name: MultiView-4D-Human-Motion-Dataset size_categories: - 1M

Multi-View Continuous 4D Human Motion Dataset

Large-Scale 1080P Multi-View Human Motion Data for AI Research & Commercial Applications

10,000+

Total Hours

2,000+

Real-world Scenes

6,000+

Subject Instances



Dataset Scale

800+

Multi-Person Interactions (Hours)

2,200+

Dual-Person Actions (Hours)

7,000+

Single-Person Actions (Hours)

📂 Dataset Structure

We provide modularly selectable annotation data covering human body parameters ranging from video-level to frame-level.

├── Dataset_Root/
│ ├── Videos/       # raw video data
│ │ ├── Duration/     # duration
│ │ ├── Scene_01/     # a complete acquisition unit
│ │ │ ├── Cam_01.mp4
│ │ │ └── ... (6 views)
│ ├── Content/       # scene content description
│ │ ├── Environment/   # environment
│ │ ├── Scene_Type/    # scene
│ │ ├── People_Count/   # number of people
│ │ ├── Action_Category/ # action
│ ├── VGGT/         # 3D Point Cloud
│ ├── Annotations/     # SMPL Parameters
│ │ ├── Scene_01.json
│ │ │ ├── "frames": [
│ │ │ │ ├──{
│ │ │ │ │ ├── "frame_id": 0,
│ │ │ │ │ ├── "smpl_params": {
│ │ │ │ │ │ ├── "global_orient": [rx, ry, rz],
│ │ │ │ │ │ ├── "body_pose": [[j1_rx, j1_ry, j1_rz],...], # 23 joints in total
│ │ │ │ │ │ ├── "transl": [tx, ty, tz],
│ │ │ │ │ ├── }
│ │ │ │ ├──}
│ │ │ ├──]
    

💡 Tip: Required fields can be freely chosen based on actual needs: multi-camera raw video data, environment, scene type, number of people, action category, duration, point cloud data (.vgt), frame-level human body parameters (SMPL).

📊 Dataset Overview


Visit Official Website:中广天择2026年高清连续多视角4D视频数据集