| --- |
| license: cc-by-nc-4.0 |
| pretty_name: VSCD |
| task_categories: |
| - image-segmentation |
| - video-classification |
| size_categories: |
| - 100GB<n<1TB |
| --- |
| |
| # VSCD: Video-based Scene Change Detection in Unaligned Scenes |
|
|
| ## Dataset Description |
|
|
| VSCD is a benchmark for **Video-based Scene Change Detection**. Given two RGB videos of the same indoor environment captured at different scene states, the task is to predict a pixel-wise change mask aligned with the query video. |
|
|
| Each environment contains five scene videos, `scene0.mp4` to `scene4.mp4`. A VSCD sample is defined by a directed scene pair: |
|
|
| ```text |
| scene0 -> scene1 |
| scene1 -> scene2 |
| scene2 -> scene3 |
| scene3 -> scene4 |
| scene4 -> scene0 |
| ``` |
|
|
| For each directed pair `sceneA -> sceneB`, `sceneA` is used as the reference video, `sceneB` is used as the query video, and `change_mask_sceneA_to_sceneB.mp4` provides the query-aligned binary change-mask video. |
|
|
| The benchmark is designed for unaligned video pairs with unconstrained camera motion, strong viewpoint mismatch, occlusions, and multiple object-level changes. Object appearances, disappearances, and relocations are treated as changes. Appearance-only variations such as illumination, shadows, and reflections are not considered semantic changes. |
|
|
| ## Dataset Structure |
|
|
| The dataset is organized into train and test splits: |
|
|
| ```text |
| vscd/ |
| ├── train/ |
| │ ├── train_<EnvironmentName>/ |
| │ │ ├── scene0.mp4 |
| │ │ ├── scene1.mp4 |
| │ │ ├── scene2.mp4 |
| │ │ ├── scene3.mp4 |
| │ │ ├── scene4.mp4 |
| │ │ ├── change_mask_scene0_to_scene1.mp4 |
| │ │ ├── change_mask_scene1_to_scene2.mp4 |
| │ │ ├── change_mask_scene2_to_scene3.mp4 |
| │ │ ├── change_mask_scene3_to_scene4.mp4 |
| │ │ └── change_mask_scene4_to_scene0.mp4 |
| │ └── ... |
| └── test/ |
| ├── test_<EnvironmentName>/ |
| │ ├── scene0.mp4 |
| │ ├── scene1.mp4 |
| │ ├── scene2.mp4 |
| │ ├── scene3.mp4 |
| │ ├── scene4.mp4 |
| │ ├── change_mask_scene0_to_scene1.mp4 |
| │ ├── change_mask_scene1_to_scene2.mp4 |
| │ ├── change_mask_scene2_to_scene3.mp4 |
| │ ├── change_mask_scene3_to_scene4.mp4 |
| │ └── change_mask_scene4_to_scene0.mp4 |
| └── ... |
| ``` |
|
|
| For example, an environment folder may look like: |
|
|
| ```text |
| test/test_BedroomScene18/ |
| ├── scene0.mp4 |
| ├── scene1.mp4 |
| ├── scene2.mp4 |
| ├── scene3.mp4 |
| ├── scene4.mp4 |
| ├── change_mask_scene0_to_scene1.mp4 |
| ├── change_mask_scene1_to_scene2.mp4 |
| ├── change_mask_scene2_to_scene3.mp4 |
| ├── change_mask_scene3_to_scene4.mp4 |
| └── change_mask_scene4_to_scene0.mp4 |
| ``` |
|
|
| ## Splits |
|
|
| - `train`: training split |
| - `test`: test split |
|
|
| Each split contains multiple environment folders. Each environment folder defines five directed video-pair samples. |
|
|
| ## Pair Definition |
|
|
| The dataset uses the following fixed directed pairs: |
|
|
| | Reference scene | Query scene | Change mask | |
| |---|---|---| |
| | `scene0.mp4` | `scene1.mp4` | `change_mask_scene0_to_scene1.mp4` | |
| | `scene1.mp4` | `scene2.mp4` | `change_mask_scene1_to_scene2.mp4` | |
| | `scene2.mp4` | `scene3.mp4` | `change_mask_scene2_to_scene3.mp4` | |
| | `scene3.mp4` | `scene4.mp4` | `change_mask_scene3_to_scene4.mp4` | |
| | `scene4.mp4` | `scene0.mp4` | `change_mask_scene4_to_scene0.mp4` | |
|
|
| For a pair `sceneA -> sceneB`: |
|
|
| - `sceneA.mp4`: reference video |
| - `sceneB.mp4`: query video |
| - `change_mask_sceneA_to_sceneB.mp4`: binary change mask video aligned with `sceneB.mp4` |
|
|
| ## Download |
|
|
| To download the full dataset: |
|
|
| ```bash |
| hf download jiae1234/vscd --repo-type dataset --local-dir ./VSCD |
| ``` |
|
|
| To download a specific file: |
|
|
| ```bash |
| hf download jiae1234/vscd test/test_BedroomScene18/scene0.mp4 --repo-type dataset --local-dir ./VSCD_sample |
| ``` |
|
|
| ## License |
|
|
| This dataset is released under the Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0). |
|
|
| The dataset may be used, shared, and adapted for non-commercial research purposes with proper attribution. |
|
|
| ## Asset Notice |
|
|
| This dataset contains only rendered video files and rendered change-mask annotations generated from simulation environments. It does not include or redistribute the original 3D assets, textures, meshes, Unreal Engine project files, simulator source assets, or asset-pack files used to generate the videos. |
|
|
| Some rendered environments were generated using AI2-THOR and Unreal Engine/Fab/Marketplace assets. Users of this dataset are granted access only to the rendered video data and annotations released in this repository, not to the underlying third-party assets. |
|
|
| ## Citation |
|
|
| If you use this dataset, please cite: |
|
|
| ```bibtex |
| @inproceedings{yoon2026vscd, |
| title={VSCD: Video-based Scene Change Detection in Unaligned Scenes}, |
| author={Yoon, Jiae and Kim, Ue-Hwan}, |
| booktitle={Proceedings of the 43rd International Conference on Machine Learning}, |
| year={2026} |
| } |
| ``` |