100+ datasets found
  1. mobilenet_face

    • kaggle.com
    Updated Feb 29, 2020
    + more versions
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    Shangqiu Li (2020). mobilenet_face [Dataset]. https://www.kaggle.com/unkownhihi/mobilenet-face/metadata
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Feb 29, 2020
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Shangqiu Li
    Description

    Dataset

    This dataset was created by Shangqiu Li

    Contents

  2. vgg-face-weights

    • kaggle.com
    Updated May 25, 2020
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    Rupak Acharya (2020). vgg-face-weights [Dataset]. https://www.kaggle.com/acharyarupak391/vggfaceweights/code
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    May 25, 2020
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Rupak Acharya
    Description

    Dataset

    This dataset was created by Rupak Acharya

    Contents

  3. h

    weights

    • huggingface.co
    Updated Jun 12, 2025
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    hug3456 (2025). weights [Dataset]. https://huggingface.co/datasets/face1234f/weights
    Explore at:
    Dataset updated
    Jun 12, 2025
    Authors
    hug3456
    Description

    face1234f/weights dataset hosted on Hugging Face and contributed by the HF Datasets community

  4. F

    East Asian Occluded Facial Image Dataset

    • futurebeeai.com
    wav
    Updated Aug 1, 2022
    + more versions
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    FutureBee AI (2022). East Asian Occluded Facial Image Dataset [Dataset]. https://www.futurebeeai.com/dataset/image-dataset/facial-images-occlusion-east-asia
    Explore at:
    wavAvailable download formats
    Dataset updated
    Aug 1, 2022
    Dataset provided by
    FutureBeeAI
    Authors
    FutureBee AI
    License

    https://www.futurebeeai.com/policies/ai-data-license-agreementhttps://www.futurebeeai.com/policies/ai-data-license-agreement

    Area covered
    East Asia
    Dataset funded by
    FutureBeeAI
    Description

    Introduction

    Welcome to the East Asian Human Face with Occlusion Dataset, carefully curated to support the development of robust facial recognition systems, occlusion detection models, biometric identification technologies, and KYC verification tools. This dataset provides real-world variability by including facial images with common occlusions, helping AI models perform reliably under challenging conditions.

    Facial Image Data

    The dataset comprises over 5,000 high-quality facial images, organized into participant-wise sets. Each set includes:

    •
    Occluded Images: 5 images per individual featuring different types of facial occlusions, masks, caps, sunglasses, or combinations of these accessories
    •
    Normal Image: 1 reference image of the same individual without any occlusion

    Diversity & Representation

    •
    Geographic Coverage: Participants from across China, Japan, Philippines, Malaysia, Singapore, Thailand, Vietnam, Indonesia, and more East Asian countries
    •
    Demographics: Individuals aged 18 to 70 years, with a 60:40 male-to-female ratio
    •
    File Formats: Images available in JPEG and HEIC formats

    Image Quality & Capture Conditions

    To ensure robustness and real-world utility, images were captured under diverse conditions:

    •
    Lighting Variations: Includes both natural and artificial lighting scenarios
    •
    Background Diversity: Indoor and outdoor backgrounds for model generalization
    •
    Device Quality: Captured using the latest smartphones to ensure high resolution and consistency

    Metadata

    Each image is paired with detailed metadata to enable advanced filtering, model tuning, and analysis:

    •Unique Participant ID
    •File Name
    •Age
    •Gender
    •Country
    •Demographic Profile
    •Type of Occlusion
    •File Format

    This rich metadata helps train models that can recognize faces even when partially obscured.

    Use Cases & Applications

    This dataset is ideal for a wide range of real-world and research-focused applications, including:

    •
    Facial Recognition under Occlusion: Improve model performance when faces are partially hidden
    •
    Occlusion Detection: Train systems to detect and classify facial accessories like masks or sunglasses
    •
    Biometric Identity Systems: Enhance verification accuracy across varying conditions
    •
    KYC & Compliance: Support face matching even when the selfie includes common occlusions.
    •
    Security & Surveillance: Strengthen access control and monitoring systems in environments with mask usage

    Secure & Ethical Collection

    •
    Data Security: Collected and processed securely on FutureBeeAI’s proprietary platform
    •
    Ethical Compliance: Follows strict guidelines for participant privacy and informed consent
    •
    Transparent Participation: All contributors provided written consent and were informed of the intended use
    <h3

  5. YOLOv3 Face Detection (weights + cfg)

    • kaggle.com
    Updated Jun 15, 2023
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    Badruddoza Kaif (2023). YOLOv3 Face Detection (weights + cfg) [Dataset]. https://www.kaggle.com/datasets/bokaif/yolov3-face
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Jun 15, 2023
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Badruddoza Kaif
    Description

    Dataset

    This dataset was created by Badruddoza Kaif

    Contents

  6. h

    weights

    • huggingface.co
    Updated Mar 30, 2025
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    Alidaneshpour (2025). weights [Dataset]. https://huggingface.co/datasets/Alidaneshpour/weights
    Explore at:
    Dataset updated
    Mar 30, 2025
    Authors
    Alidaneshpour
    Description

    Alidaneshpour/weights dataset hosted on Hugging Face and contributed by the HF Datasets community

  7. F

    Caucasian Occluded Facial Image Dataset

    • futurebeeai.com
    wav
    Updated Aug 1, 2022
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    FutureBee AI (2022). Caucasian Occluded Facial Image Dataset [Dataset]. https://www.futurebeeai.com/dataset/image-dataset/facial-images-occlusion-caucasian
    Explore at:
    wavAvailable download formats
    Dataset updated
    Aug 1, 2022
    Dataset provided by
    FutureBeeAI
    Authors
    FutureBee AI
    License

    https://www.futurebeeai.com/policies/ai-data-license-agreementhttps://www.futurebeeai.com/policies/ai-data-license-agreement

    Dataset funded by
    FutureBeeAI
    Description

    Introduction

    Welcome to the Caucasian Human Face with Occlusion Dataset, carefully curated to support the development of robust facial recognition systems, occlusion detection models, biometric identification technologies, and KYC verification tools. This dataset provides real-world variability by including facial images with common occlusions, helping AI models perform reliably under challenging conditions.

    Facial Image Data

    The dataset comprises over 3,000 high-quality facial images, organized into participant-wise sets. Each set includes:

    •
    Occluded Images: 5 images per individual featuring different types of facial occlusions, masks, caps, sunglasses, or combinations of these accessories
    •
    Normal Image: 1 reference image of the same individual without any occlusion

    Diversity & Representation

    •
    Geographic Coverage: Participants from across Spain, Italy, Turkey, Germany, France, and more Caucasian countries
    •
    Demographics: Individuals aged 18 to 70 years, with a 60:40 male-to-female ratio
    •
    File Formats: Images available in JPEG and HEIC formats

    Image Quality & Capture Conditions

    To ensure robustness and real-world utility, images were captured under diverse conditions:

    •
    Lighting Variations: Includes both natural and artificial lighting scenarios
    •
    Background Diversity: Indoor and outdoor backgrounds for model generalization
    •
    Device Quality: Captured using the latest smartphones to ensure high resolution and consistency

    Metadata

    Each image is paired with detailed metadata to enable advanced filtering, model tuning, and analysis:

    •Unique Participant ID
    •File Name
    •Age
    •Gender
    •Country
    •Demographic Profile
    •Type of Occlusion
    •File Format

    This rich metadata helps train models that can recognize faces even when partially obscured.

    Use Cases & Applications

    This dataset is ideal for a wide range of real-world and research-focused applications, including:

    •
    Facial Recognition under Occlusion: Improve model performance when faces are partially hidden
    •
    Occlusion Detection: Train systems to detect and classify facial accessories like masks or sunglasses
    •
    Biometric Identity Systems: Enhance verification accuracy across varying conditions
    •
    KYC & Compliance: Support face matching even when the selfie includes common occlusions.
    •
    Security & Surveillance: Strengthen access control and monitoring systems in environments with mask usage

    Secure & Ethical Collection

    •
    Data Security: Collected and processed securely on FutureBeeAI’s proprietary platform
    •
    Ethical Compliance: Follows strict guidelines for participant privacy and informed consent
    •
    Transparent Participation: All contributors provided written consent and were informed of the intended use

    Dataset Updates &

  8. f

    The RMSE results for each facial component by different methods.

    • plos.figshare.com
    xls
    Updated Jun 4, 2023
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    Yang Yang; Shaoyi Du; Zhuo Chen (2023). The RMSE results for each facial component by different methods. [Dataset]. http://doi.org/10.1371/journal.pone.0159376.t001
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 4, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Yang Yang; Shaoyi Du; Zhuo Chen
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    The RMSE results for each facial component by different methods.

  9. h

    weights-all-small

    • huggingface.co
    Updated Feb 12, 2025
    + more versions
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    Duszenko (2025). weights-all-small [Dataset]. https://huggingface.co/datasets/jacekduszenko/weights-all-small
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Feb 12, 2025
    Authors
    Duszenko
    Description

    jacekduszenko/weights-all-small dataset hosted on Hugging Face and contributed by the HF Datasets community

  10. Weight for face recognition

    • kaggle.com
    Updated Jul 26, 2021
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    hungkhoi99121816 (2021). Weight for face recognition [Dataset]. https://www.kaggle.com/hungkhoi99121816/weight-for-face-recognition/code
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Jul 26, 2021
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    hungkhoi99121816
    Description

    Dataset

    This dataset was created by hungkhoi99121816

    Contents

  11. f

    Dataset for all participants.

    • plos.figshare.com
    zip
    Updated May 30, 2023
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    Karin Wolffhechel; Amanda C. Hahn; Hanne Jarmer; Claire I. Fisher; Benedict C. Jones; Lisa M. DeBruine (2023). Dataset for all participants. [Dataset]. http://doi.org/10.1371/journal.pone.0140347.s001
    Explore at:
    zipAvailable download formats
    Dataset updated
    May 30, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Karin Wolffhechel; Amanda C. Hahn; Hanne Jarmer; Claire I. Fisher; Benedict C. Jones; Lisa M. DeBruine
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Files hold anonymized information on all participants for BMI, age, height, weight, facial metrics and shape and color principal components. (ZIP)

  12. F

    Hispanic Occluded Facial Image Dataset

    • futurebeeai.com
    wav
    Updated Aug 1, 2022
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    FutureBee AI (2022). Hispanic Occluded Facial Image Dataset [Dataset]. https://www.futurebeeai.com/dataset/image-dataset/facial-images-occlusion-hispanic
    Explore at:
    wavAvailable download formats
    Dataset updated
    Aug 1, 2022
    Dataset provided by
    FutureBeeAI
    Authors
    FutureBee AI
    License

    https://www.futurebeeai.com/policies/ai-data-license-agreementhttps://www.futurebeeai.com/policies/ai-data-license-agreement

    Dataset funded by
    FutureBeeAI
    Description

    Introduction

    Welcome to the Hispanic Human Face with Occlusion Dataset, carefully curated to support the development of robust facial recognition systems, occlusion detection models, biometric identification technologies, and KYC verification tools. This dataset provides real-world variability by including facial images with common occlusions, helping AI models perform reliably under challenging conditions.

    Facial Image Data

    The dataset comprises over 3,000 high-quality facial images, organized into participant-wise sets. Each set includes:

    •
    Occluded Images: 5 images per individual featuring different types of facial occlusions, masks, caps, sunglasses, or combinations of these accessories
    •
    Normal Image: 1 reference image of the same individual without any occlusion

    Diversity & Representation

    •
    Geographic Coverage: Participants from across Argentina, Brazil, Costa Rica, Ecuador, Colombia, Peru, and more Hispanic countries
    •
    Demographics: Individuals aged 18 to 70 years, with a 60:40 male-to-female ratio
    •
    File Formats: Images available in JPEG and HEIC formats

    Image Quality & Capture Conditions

    To ensure robustness and real-world utility, images were captured under diverse conditions:

    •
    Lighting Variations: Includes both natural and artificial lighting scenarios
    •
    Background Diversity: Indoor and outdoor backgrounds for model generalization
    •
    Device Quality: Captured using the latest smartphones to ensure high resolution and consistency

    Metadata

    Each image is paired with detailed metadata to enable advanced filtering, model tuning, and analysis:

    •Unique Participant ID
    •File Name
    •Age
    •Gender
    •Country
    •Demographic Profile
    •Type of Occlusion
    •File Format

    This rich metadata helps train models that can recognize faces even when partially obscured.

    Use Cases & Applications

    This dataset is ideal for a wide range of real-world and research-focused applications, including:

    •
    Facial Recognition under Occlusion: Improve model performance when faces are partially hidden
    •
    Occlusion Detection: Train systems to detect and classify facial accessories like masks or sunglasses
    •
    Biometric Identity Systems: Enhance verification accuracy across varying conditions
    •
    KYC & Compliance: Support face matching even when the selfie includes common occlusions.
    •
    Security & Surveillance: Strengthen access control and monitoring systems in environments with mask usage

    Secure & Ethical Collection

    •
    Data Security: Collected and processed securely on FutureBeeAI’s proprietary platform
    •
    Ethical Compliance: Follows strict guidelines for participant privacy and informed consent
    •
    Transparent Participation: All contributors provided written consent and were informed of the intended use

    Dataset

  13. h

    Chatbot-Model-Cleaned-Weights

    • huggingface.co
    Updated Nov 9, 2024
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    Prithiv Sakthi (2024). Chatbot-Model-Cleaned-Weights [Dataset]. https://huggingface.co/datasets/prithivMLmods/Chatbot-Model-Cleaned-Weights
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Nov 9, 2024
    Authors
    Prithiv Sakthi
    License

    Apache License, v2.0https://www.apache.org/licenses/LICENSE-2.0
    License information was derived automatically

    Description

    prithivMLmods/Chatbot-Model-Cleaned-Weights dataset hosted on Hugging Face and contributed by the HF Datasets community

  14. Faces Dataset all at one place

    • kaggle.com
    Updated Feb 24, 2021
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    Shanmukh (2021). Faces Dataset all at one place [Dataset]. https://www.kaggle.com/datasets/shanmukh05/vggface-using-tripletloss/versions/18
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Feb 24, 2021
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Shanmukh
    License

    Attribution-NonCommercial 4.0 (CC BY-NC 4.0)https://creativecommons.org/licenses/by-nc/4.0/
    License information was derived automatically

    Description

    Context

    As name of dataset says, this dataset contains the variety of face datasets available.

    Content

    CFP data folder: This folder consists of around 5000 images distributed among 500 persons (10 each). source celebs folder This folder contains images 100 bollywood actors. A total of 10029 images are present. source images resolute This folder contains images of over 664 persons across the world. (Approximately size is 1.3GB ) dataset folder This folder consists low resolution images of 158 persons. crop faces folder This folder contains cropped faces of dataset folder. Cropping is done with MTCNN library.

    vgg face weights h5 file Pretrained weights of VGG Facenet model. For more details visit VGG face recognition

  15. h

    weight-prefer-role-1

    • huggingface.co
    Updated May 20, 2025
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    flashNeko (2025). weight-prefer-role-1 [Dataset]. https://huggingface.co/datasets/tools-o/weight-prefer-role-1
    Explore at:
    Dataset updated
    May 20, 2025
    Authors
    flashNeko
    Description

    tools-o/weight-prefer-role-1 dataset hosted on Hugging Face and contributed by the HF Datasets community

  16. h

    openvla-lora-weights

    • huggingface.co
    Updated May 28, 2025
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    Ngo Thanh Dat (2025). openvla-lora-weights [Dataset]. https://huggingface.co/datasets/moewie94/openvla-lora-weights
    Explore at:
    Dataset updated
    May 28, 2025
    Authors
    Ngo Thanh Dat
    Description

    moewie94/openvla-lora-weights dataset hosted on Hugging Face and contributed by the HF Datasets community

  17. India Retail Price Index: Industrial Workers: 2001p: Weights: Personal Care...

    • ceicdata.com
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    CEICdata.com, India Retail Price Index: Industrial Workers: 2001p: Weights: Personal Care and Effects: Face Cream [Dataset]. https://www.ceicdata.com/en/india/retail-price-index-industrial-workers-2001100-weights-miscellaneous-personal-care-and-effects/retail-price-index-industrial-workers-2001p-weights-personal-care-and-effects-face-cream
    Explore at:
    Dataset provided by
    CEIC Data
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Oct 1, 2017 - Sep 1, 2018
    Area covered
    India
    Variables measured
    Domestic Trade Price
    Description

    India Retail Price Index: Industrial Workers: 2001p: Weights: Personal Care and Effects: Face Cream data was reported at 0.150 % in Oct 2018. This stayed constant from the previous number of 0.150 % for Sep 2018. India Retail Price Index: Industrial Workers: 2001p: Weights: Personal Care and Effects: Face Cream data is updated monthly, averaging 0.150 % from Jan 2006 (Median) to Oct 2018, with 154 observations. The data reached an all-time high of 0.150 % in Oct 2018 and a record low of 0.150 % in Oct 2018. India Retail Price Index: Industrial Workers: 2001p: Weights: Personal Care and Effects: Face Cream data remains active status in CEIC and is reported by Labour Bureau Government of India. The data is categorized under India Premium Database’s Inflation – Table IN.IG031: Retail Price Index: Industrial Workers: 2001=100: Weights: Miscellaneous: Personal Care and Effects.

  18. h

    weight-prefer-role-7

    • huggingface.co
    Updated May 20, 2025
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    flashNeko (2025). weight-prefer-role-7 [Dataset]. https://huggingface.co/datasets/tools-o/weight-prefer-role-7
    Explore at:
    Dataset updated
    May 20, 2025
    Authors
    flashNeko
    Description

    tools-o/weight-prefer-role-7 dataset hosted on Hugging Face and contributed by the HF Datasets community

  19. India WPI: Wt: Mfg: CC: SC: Face/Body Powder

    • ceicdata.com
    Updated Dec 10, 2011
    + more versions
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    CEICdata.com (2011). India WPI: Wt: Mfg: CC: SC: Face/Body Powder [Dataset]. https://www.ceicdata.com/en/india/wholesale-price-index-201112100-weights-manufactured-products-chemicals-and-chemical-products/wpi-wt-mfg-cc-sc-facebody-powder
    Explore at:
    Dataset updated
    Dec 10, 2011
    Dataset provided by
    CEIC Data
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Nov 1, 2017 - Oct 1, 2018
    Area covered
    India
    Description

    India WPI: Wt: Mfg: CC: SC: Face/Body Powder data was reported at 0.004 % in Oct 2018. This stayed constant from the previous number of 0.004 % for Sep 2018. India WPI: Wt: Mfg: CC: SC: Face/Body Powder data is updated monthly, averaging 0.004 % from Apr 2012 (Median) to Oct 2018, with 79 observations. The data reached an all-time high of 0.004 % in Oct 2018 and a record low of 0.004 % in Oct 2018. India WPI: Wt: Mfg: CC: SC: Face/Body Powder data remains active status in CEIC and is reported by Ministry of Commerce and Industry. The data is categorized under Global Database’s India – Table IN.IH044: Wholesale Price Index: 2011-12=100: Weights: Manufactured Products: Chemicals and Chemical Products.

  20. h

    weight-prefer-role-6

    • huggingface.co
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    flashNeko, weight-prefer-role-6 [Dataset]. https://huggingface.co/datasets/tools-o/weight-prefer-role-6
    Explore at:
    Authors
    flashNeko
    License

    Apache License, v2.0https://www.apache.org/licenses/LICENSE-2.0
    License information was derived automatically

    Description

    tools-o/weight-prefer-role-6 dataset hosted on Hugging Face and contributed by the HF Datasets community

Share
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Click to copy link
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Close
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Shangqiu Li (2020). mobilenet_face [Dataset]. https://www.kaggle.com/unkownhihi/mobilenet-face/metadata
Organization logo

mobilenet_face

Weights for mobilenet face extractor.

Explore at:
CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
Dataset updated
Feb 29, 2020
Dataset provided by
Kagglehttp://kaggle.com/
Authors
Shangqiu Li
Description

Dataset

This dataset was created by Shangqiu Li

Contents

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