Datasets:

facebook
/

SACo-VEval

extra_gated_fields:
  First Name: text
  Last Name: text
  Date of birth: date_picker
  Country: country
  Affiliation: text
  Job title:
    type: select
    options:
      - Student
      - Research Graduate
      - AI researcher
      - AI developer/engineer
      - Reporter
      - Other
  geo: ip_location
  By clicking Submit below I accept the terms of the license and acknowledge that the information I provide will be collected stored processed and shared in accordance with the Meta Privacy Policy: checkbox
extra_gated_description: >-
  The information you provide will be collected, stored, processed and shared in
  accordance with the [Meta Privacy
  Policy](https://www.facebook.com/privacy/policy/).
extra_gated_button_content: Submit
language:
  - en
license: other
pretty_name: SACo-VEval
configs:
  - config_name: SACo-VEval SA-V
    data_files:
      - split: test
        path: annotation/saco_veval_sav_test.json
      - split: val
        path: annotation/saco_veval_sav_val.json
  - config_name: SACo-VEval YT-Temporal-1B
    data_files:
      - split: test
        path: annotation/saco_veval_yt1b_test.json
      - split: val
        path: annotation/saco_veval_yt1b_val.json
  - config_name: SACo-VEval SmartGlasses
    data_files:
      - split: test
        path: annotation/saco_veval_smartglasses_test.json
      - split: val
        path: annotation/saco_veval_smartglasses_val.json

SA-Co/VEval Dataset

License each domain has its own License

SA-Co/VEval - SA-V: CC-BY-NC 4.0
SA-Co/VEval - YT-Temporal-1B: CC-BY-NC 4.0
SA-Co/VEval - SmartGlasses: CC-by-4.0

SA-Co/VEval is an evaluation dataset comprising of 3 domains, each domain has a val and test split.

SA-Co/VEval - SA-V: videos are from the SA-V dataset
SA-Co/VEval - YT-Temporal-1B: videos are from the YT-Temporal-1B
SA-Co/VEval - SmartGlasses: egocentric videos from Smart Glasses

This Hugging Face dataset repo contains the following contents:

datasets/facebook/SACo-VEval/tree/main/
├── annotation/
│   ├── saco_veval_sav_test.json
│   ├── saco_veval_sav_val.json
│   ├── saco_veval_smartglasses_test.json
│   ├── saco_veval_smartglasses_val.json
│   ├── saco_veval_yt1b_test.json
│   ├── saco_veval_yt1b_val.json
└── media/
    ├── saco_sg.tar.gz
    └── yt1b_start_end_time.json

annotation
- all the GT json files
media
- saco_sg.tar.gz: the preprocessed JPEGImages for SA-Co/VEval - SmartGlasses
- yt1b_start_end_time.json: the Youtube video ids and the start and end time used in SA-Co/VEval - YT-Temporal-1B

More detail to prepare the complete SA-Co/VEval Dataset can be found in the SAM 3 Github.

Annotation Format

The format is similar to the YTVIS format.

In the annotation json, e.g. saco_veval_sav_test.json there are 5 fields:

info:
- A dict containing the dataset info
- E.g. {'version': 'v1', 'date': '2025-09-24', 'description': 'SA-Co/VEval SA-V Test'}
videos
- A list of videos that are used in the current annotation json
- It contains {id, video_name, file_names, height, width, length}
annotations
- A list of positive masklets and their related info
- It contains {id, segmentations, bboxes, areas, iscrowd, video_id, height, width, category_id, noun_phrase}
  - video_id should match to the videos - id field above
  - category_id should match to the categories - id field below
  - segmentations is a list of RLE
categories
- A globally used noun phrase id map, which is true across all 3 domains.
- It contains {id, name}
  - name is the noun phrase
video_np_pairs
- A list of video-np pairs, including both positive and negative used in the current annotation json
- It contains {id, video_id, category_id, noun_phrase, num_masklets}
  - video_id should match the videos - id above
  - category_id should match the categories - id above
  - when num_masklets > 0 it is a positive video-np pair, and the presenting masklets can be found in the annotations field
  - when num_masklets = 0 it is a negative video-np pair, meaning no masklet presenting at all

data {
    "info": info
    "videos": [video]
    "annotations": [annotation]
    "categories": [category]
    "video_np_pairs": [video_np_pair]
}
video {
    "id": int
    "video_name": str  # e.g. sav_000000
    "file_names": List[str]
    "height": int
    "width": width
    "length": length
}
annotation {
    "id": int
    "segmentations": List[RLE]
    "bboxes": List[List[int, int, int, int]]
    "areas": List[int]
    "iscrowd": int
    "video_id": str
    "height": int
    "width": int
    "category_id": int
    "noun_phrase": str
}
category {
    "id": int
    "name": str
}
video_np_pair {
    "id": int
    "video_id": str
    "category_id": int
    "noun_phrase": str
    "num_masklets" int
}

SAM 3 Github sam3/examples/saco_veval_vis_example.ipynb shows some examples of the data format and data visualization.