The dataset viewer is not available for this dataset.
Error code: ConfigNamesError
Exception: RuntimeError
Message: Dataset scripts are no longer supported, but found silicone-masks-biometric-attacks.py
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/dataset/config_names.py", line 66, in compute_config_names_response
config_names = get_dataset_config_names(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 161, in get_dataset_config_names
dataset_module = dataset_module_factory(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1031, in dataset_module_factory
raise e1 from None
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 989, in dataset_module_factory
raise RuntimeError(f"Dataset scripts are no longer supported, but found {filename}")
RuntimeError: Dataset scripts are no longer supported, but found silicone-masks-biometric-attacks.pyNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
Silicone Masks Biometric Attack Dataset
The anti spoofing dataset consists of videos of individuals and attacks with printed 2D masks and silicone masks . Videos are filmed in different lightning conditions (in a dark room, daylight, light room and nightlight). Dataset includes videos of people with different attributes (glasses, mask, hat, hood, wigs and mustaches for men).
The dataset comprises videos of genuine facial presentations using various methods, including 3D masks and photos, as well as real and spoof faces. It proposes a novel approach that learns and extracts facial features to prevent spoofing attacks, based on deep neural networks and advanced biometric techniques.
Our results show that this technology works effectively in securing most applications and prevents unauthorized access by distinguishing between genuine and spoofed inputs. Additionally, it addresses the challenging task of identifying unseen spoofing cues, making it one of the most effective techniques in the field of anti-spoofing research.
💴 For Commercial Usage: Full version of the dataset includes 5792 videos, leave a request on TrainingData to buy the dataset
Types of videos in the dataset:
- real - real video of the person
- outline -video of the person wearing a printed 2D mask
- silicone - video of the person wearing a silicone mask
Types and number of videos in the full dataset:
- 2885 real videos of people
- 2859 videos of people wearing silicone mask
- 48 videos of people wearing a 2D mask.
Gender of people in the dataset:
- women: 2685
- men: 3107
The dataset serves as a valuable resource for computer vision, anti-spoofing tasks, video analysis, and security systems. It allows for the development of algorithms and models that can effectively detect attacks.
Studying the dataset may lead to the development of improved security systems, surveillance technologies, and solutions to mitigate the risks associated with masked individuals carrying out attacks.
💴 Buy the Dataset: This is just an example of the data. Leave a request on https://trainingdata.pro/datasets to discuss your requirements, learn about the price and buy the dataset
Content
- real - contains of real videos of people,
- mask - contains of videos with people wearing a printed 2D mask,
- silicone - contains of videos with people wearing a silicone mask,
- dataset_info.csvl - includes the information about videos in the dataset
File with the extension .csv
- video: link to the video,
- type: type of the video
Attacks might be collected in accordance with your requirements.
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More datasets in TrainingData's Kaggle account: https://www.kaggle.com/trainingdatapro/datasets
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