| --- |
| license: mit |
| pretty_name: The Multiview Moving Camera Dataset (MMCD) |
| viewer: false |
| source_datasets: |
| - original |
| size_categories: |
| - n<1K |
| tags: |
| - video-stitching |
| - image-stitching |
| - multi-view |
| - moving-cameras |
| - panoramic-video |
| - keypoints |
| --- |
| |
| # The Multiview Moving Camera Dataset (MMCD) |
|
|
| ## Dataset Summary |
|
|
| To our knowledge, no available dataset supports multiple video stitching with *N* > 2 freely moving cameras. |
| Thus, we created MMCD, a new multiview dataset. MMCD contains 53 scenes, each with 3–6 approximately |
| synchronized handheld videos captured on diverse mobile devices under varied environmental and lighting conditions. |
| Camera models, resolutions, and motions vary substantially. Overall, MMCD contains 221 videos and 47,040 frames. |
|
|
| To facilitate quantitative evaluation, we manually annotated keypoints in the overlap regions of the first frames |
| and propagated them through the sequences using CoTracker3. The annotations are used solely for evaluation. |
|
|
| The dataset is provided as a single file, `MMCD.zip`. Unzipping it gives the following structure: |
|
|
| ``` |
| MMCD/ |
| ├── frames/ |
| │ └── <scene>/ |
| │ ├── video0/ |
| │ ├── video1/ |
| │ └── ... |
| └── kps_annotations/ |
| └── <scene>/ |
| ├── kps_<scene>.pt |
| └── pred_visibility_<scene>.pt |
| ``` |
|
|
| *N* - the number of videos in the scene. |
|
|
| ## Data Fields |
|
|
| In addition to the frames folder, each scene has 2 tensors, one for the keypoint annotations and one for the visibility flags. |
|
|
| - `frames/<scene>/video<i>/`: the frames of video *i* of the scene. |
| - `kps_annotations/<scene>/kps_<scene>.pt`: a PyTorch tensor of shape `[num_frames, N, keypoint_index, 2]`, with the 2D position of every |
| keypoint in every frame of every video, in pixels of the original frames. |
| - `kps_annotations/<scene>/pred_visibility_<scene>.pt`: a PyTorch tensor of shape `[num_frames, N, keypoint_index]`, with the visibility |
| flags predicted by CoTracker3: 1 if the keypoint is visible in that video's frame, and 0 otherwise. |
|
|
| ## Data Statistics |
|
|
| MMCD has no train/test splits; all of the scenes are used for evaluation. It is divided into 4 categories based on |
| *N*, the number of cameras: |
|
|
| | | *N* = 3 | *N* = 4 | *N* = 5 | *N* = 6 | Total | |
| | --- | :---: | :---: | :---: | :---: | :---: | |
| | Scenes | 22 | 10 | 11 | 10 | 53 | |
|
|
| All of the videos are 30 fps. |
|
|
| <details> |
| <summary><b>N = 3</b> (22 scenes)</summary> |
|
|
| | Scene | Length | Resolution (H×W) | |
| | --- | :---: | :---: | |
| | scene_1 | 9 sec | 478×848 | |
| | scene_2 | 6 sec | 478×848 | |
| | scene_4 | 7 sec | 478×848 | |
| | scene_6 | 8 sec | 478×848 | |
| | scene_7 | 9 sec | 478×848 | |
| | scene_8 | 10 sec | 478×848 | |
| | scene_9 | 6 sec | 478×848 | |
| | scene_10 | 7 sec | 478×848 | |
| | scene_12 | 8 sec | 478×848 | |
| | scene_13 | 9 sec | 478×848 | |
| | scene_15 | 10 sec | 478×848 | |
| | scene_18 | 7 sec | 478×848 | |
| | scene_19 | 8 sec | 478×848 | |
| | scene_20 | 9 sec | 478×848 | |
| | scene_21 | 10 sec | 478×848 | |
| | scene_29 | 6 sec | 480×840 | |
| | scene_39 | 10 sec | 480×840 | |
| | scene_67 | 10 sec | 480×840 | |
| | scene_69 | 9 sec | 480×840 | |
| | scene_70 | 10 sec | 480×840 | |
| | scene_106 | 5 sec | 480×840 | |
| | scene_110 | 9 sec | 1200×800 | |
|
|
| </details> |
|
|
| <details> |
| <summary><b>N = 4</b> (10 scenes)</summary> |
|
|
| | Scene | Length | Resolution (H×W) | |
| | --- | :---: | :---: | |
| | scene_25 | 5 sec | 480×840 | |
| | scene_30 | 5 sec | 480×840 | |
| | scene_31 | 6 sec | 480×840 | |
| | scene_35 | 6 sec | 480×840 | |
| | scene_47 | 7 sec | 480×840 | |
| | scene_49 | 5 sec | 480×840 | |
| | scene_54 | 8 sec | 480×840 | |
| | scene_64 | 6 sec | 480×840 | |
| | scene_81 | 8 sec | 480×840 | |
| | scene_92 | 10 sec | 450×478 | |
|
|
| </details> |
|
|
| <details> |
| <summary><b>N = 5</b> (11 scenes)</summary> |
|
|
| | Scene | Length | Resolution (H×W) | |
| | --- | :---: | :---: | |
| | scene_33 | 7 sec | 480×840 | |
| | scene_46 | 8 sec | 480×840 | |
| | scene_51 | 7 sec | 480×840 | |
| | scene_62 | 9 sec | 480×840 | |
| | scene_63 | 7 sec | 480×840 | |
| | scene_65 | 5 sec | 480×840 | |
| | scene_66 | 7 sec | 480×840 | |
| | scene_72 | 8 sec | 480×840 | |
| | scene_76 | 6 sec | 480×840 | |
| | scene_77 | 6 sec | 480×840 | |
| | scene_98 | 6 sec | 480×840 | |
| |
| </details> |
| |
| <details> |
| <summary><b>N = 6</b> (10 scenes)</summary> |
| |
| | Scene | Length | Resolution (H×W) | |
| | --- | :---: | :---: | |
| | scene_27 | 7 sec | 480×840 | |
| | scene_50 | 5 sec | 480×840 | |
| | scene_52 | 6 sec | 480×840 | |
| | scene_53 | 5 sec | 480×840 | |
| | scene_55 | 7 sec | 480×840 | |
| | scene_57 | 6 sec | 480×840 | |
| | scene_58 | 7 sec | 480×840 | |
| | scene_59 | 6 sec | 480×840 | |
| | scene_60 | 5 sec | 480×840 | |
| | scene_101 | 9 sec | 480×840 | |
| |
| </details> |
| |
| ## Personal and Sensitive Information |
| |
| The dataset does not contain personal or sensitive information. |
| |
| ## Citation |
| |
| ```bibtex |
| @inproceedings{Ifergane:NeurIPS:2026:MViS, |
| title = {Video Stitching from Multiple Moving Cameras}, |
| author = {Ifergane, Shira and Amoyal, Roy and Benishay, Shahar and Freifeld, Oren}, |
| booktitle = {Advances in Neural Information Processing Systems (NeurIPS)}, |
| year = {2026} |
| } |
| ``` |
| |
