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-# Scene-Decoupled Video Dataset
-
-TL;DR: The Scene-Decoupled Video Dataset, introduced in CineScene, is a large-scale synthetic dataset for **video generation with decoupled scene**, which encompasses diverse scenes, subjects, and camera movements. This dataset contains camera trajectories, equirectangular panorama (scene image), and videos with/without dynamic subject. The data is organized into "With Human" (whuman) and "Without Human" (wohuman) categories, while panoramas are scene-decoupled and shared across both.
-
-## 1. Directory Tree
-
-```text
-.
-├── camera/                           # Camera trajectories and metadata
-│   ├── whuman/                       # Sequences containing human characters
-│   │   └── <scene_id>/               # e.g., scene1_3x3_loc1_scene_AncientTempleEnv/
-│   │       └── <scene_id>_cam.json   # Camera parameters
-│   └── wohuman/                      # Sequences with environment only
-│       └── <scene_id>/
-│           └── <scene_id>_cam.json
-│
-├── panorama/                         # Scene-decoupled environment maps
-│   └── <scene_id>/                   # Shared between whuman and wohuman
-│       └── <scene_id>_pano.jpeg      # 360° Equirectangular panoramic image
-│
-└── video/                            # Rendered video sequences (MP4)
-    ├── whuman/                       # Videos with human characters
-    │   └── <scene_id>/
-    │       ├── <scene_id>_01_24mm.mp4 # Sub-sequences (01, 02, etc.)
-    │       ├── <scene_id>_02_24mm.mp4
-    │       └── ...
-    └── wohuman/                      # Videos without human characters
-        └── <scene_id>/
-            ├── <scene_id>_01_24mm.mp4
-            ├── ...
-
-```
-
-
-
-## 2. Dataset Statistics
-
-*   **Total Scale**: 46,816 videos.
-*   **Scenes**: 6,688 scenes (comprising 3,344 *whuman* and 3,344 *wohuman* scenes) across 35 high-quality 3D environments.
-*   **Trajectories**: 46,816 camera paths (7 distinct camera trajectories per scene).
-*   **Panorama**: 360° Equirectangular images for every scene, providing a complete background reference for scene conditioning.
-
-| Property | Value |
-| :--- | :--- |
-| **Video Resolution** | 672 x 384 |
-| **Frame Count** | 81 frames per video |
-| **Frame Rate** | 15 FPS |
-| **View Change Range** | Up to 75° |
-| **Decoupled Scene** | 360° Equirectangular (Panorama) |
-| **Panorama Resolution** | 2048 x 1024 |
-
-
-## 3. Dataset Construction
-
-We follow the asset collection pipeline established by **RecamMaster**, but introduce three significant enhancements to support more complex generative tasks:
-
-1.  **Decoupled Scenes**: We provide static 360° panoramic images (Equirectangular) for every scene. This allows for explicit background conditioning and facilitates novel view synthesis from any angle.
-2.  **Extended Camera Range**: Our dataset covers significantly larger view changes (approx. **75°**) compared to the 5–60° range provided in previous datasets [1].
-3.  **Paired Subject/Background Data**: Every scene includes both "with-subject" (*whuman*) and "background-only" (*wohuman*) video sequences. This paired data is ideal for training models on subject-background decoupling, motion transfer, and cinematic composition.
-
-## 4. useful script
-
-- download
-
-```bash
-sudo apt-get install git-lfs
-git lfs install
-git clone https://huggingface.co/datasets/KwaiVGI/Scene-Decoupled-Video-Dataset
-cat Scene-Decoupled-Video-Dataset.part* > Scene-Decoupled-Video-Dataset.tar.gz
-tar -xvf Scene-Decoupled-Video-Dataset.tar.gz
-```
-
-- camera visualization
-
-  To visualize the camera, please refer to [here.](https://huggingface.co/datasets/KlingTeam/MultiCamVideo-Dataset/blob/main/vis_cam.py)
-
-- Perspective Projection
-To extract perspective frames from the panoramic images:
-
-  ```
-  python extract_scene_from_panorama.py
-  ```
-
-  
-
-References
-[1] Bai J, Xia M, Fu X, et al. Recammaster: Camera-controlled generative rendering from a single video[J]. arXiv preprint arXiv:2503.11647, 2025.