…The dataset is audio-visual, so is also useful for a number of other applications, for example – visual speech synthesis, speech separation, cross-modal transfer from face to voice or vice versa and training face recognition from video to complement existing face recognition datasets.
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This is a 16.2-million frame (50-hour) multimodal dataset of two-person face-to-face spontaneous conversations. This dataset features synchronized body and finger motion as well as audio data.
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The MERL-RAV (MERL Reannotation of AFLW with Visibility) Dataset contains over 19,000 face images in a full range of head poses. Each face is manually labeled with the ground-truth locations of 68 landmarks, with the additional information of whether each landmark is unoccluded, self-occluded (due to extreme head poses), or externally
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Description K-pop Idol Dataset - Female (KID-F) is the first dataset of K-pop idol high quality face images. It consists of about 6,000 high quality face images at 512x512 resolution and identity labels for each image. We collected about 90,000 K-pop female idol images and crop the face from each image. And we classified high quality face images. As a result, there are about 6,000 high quality face images in this dataset. There are 300 test datasets for a benchmark. You can use these degraded test images for testing face super resolution performance. We also provide identity labels for each image.
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…The original dataset contained both a "Faces" and "Faces Easy" class, with each consisting of different versions of the same images. The "Faces" class has been removed from N-Caltech101 to avoid confusion, leaving 100 object classes plus a background class.
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…The segments are of varying length, between 3 and 10 seconds long, and in each clip the only visible face in the video and audible sound in the soundtrack belong to a single speaking person. In total, the dataset contains roughly 4700 hours of video segments with approximately 150,000 distinct speakers, spanning a wide variety of people, languages and face poses.
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The LAGENDA dataset is a large-scale dataset with age and gender annotations for face and body bounding boxes. The dataset consists of 67,159 images from the Open Images Dataset and comprises 84,192 pairs (FaceCrop, BodyCrop).
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…The participant ratings, physiological recordings and face video of an experiment where 32 volunteers watched a subset of 40 of the above music videos. For 22 participants frontal face video was also recorded.
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The source images of UAGD is manually selected from APPA-REAL, UTKFace and AgeDB datasets very carefully, which means only face images that are having large poses, containing noise pixels, bearing various UAGD has almost the same number of female and male images in each age, about 75 female and 75 male, total 150 face.
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Animal FacesHQ (AFHQ) is a dataset of animal faces consisting of 15,000 high-quality images at 512 × 512 resolution.
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The Radboud Faces Database (RaFD) is a set of pictures of 67 models (both adult and children, males and females) displaying 8 emotional expressions.
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…(1) vesteinn/icelandic-ner-MIM-GOLD-NER · Datasets at Hugging Face. https://huggingface.co/datasets/vesteinn/icelandic-ner-MIM-GOLD-NER. (2) svanhvit/icelandic-ner-MIM-GOLD-NER · Datasets at Hugging Face. https://huggingface.co/datasets/svanhvit/icelandic-ner-MIM-GOLD-NER. (3) vesteinn/icelandic-ner-MIM-GOLD-NER at main - Hugging Face. https://huggingface.co/datasets/vesteinn/icelandic-ner-MIM-GOLD-NER
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…MultiNLI offers ten distinct genres (Face-to-face, Telephone, 9/11, Travel, Letters, Oxford University Press, Slate, Verbatim, Goverment and Fiction) of written and spoken English data.
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This is a synthetic dataset containing full images (instead of only cropped faces) that provides ground truth 3D gaze directions for multiple people in one image.
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A high-resolution version of VGGFace2 for academic face editing purposes. This project uses GFPGAN for image restoration and insightface for data preprocessing (crop and align).
The ORL Database of Faces contains 400 images from 40 distinct subjects. Download dataset from Kaggle: https://www.kaggle.com/datasets/kasikrit/att-database-of-faces
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…The existence of such large weak-labeled databases has gained importance in the training of face recognition algorithms. Starting with the publicly available YFCC100M, we propose a weakly-labeled subset for multi-label face recognition for self-supervised methods.
4DFAB is a large scale database of dynamic high-resolution 3D faces which consists of recordings of 180 subjects captured in four different sessions spanning over a five-year period (2012 - 2017), resulting The database can be used for both face and facial expression recognition, as well as behavioural biometrics. It can also be used to learn very powerful blendshapes for parametrising facial behaviour.
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The HELEN dataset is composed of 2330 face images of 400×400 pixels with labeled facial components generated through manually-annotated contours along eyes, eyebrows, nose, lips and jawline.
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The Human-Parts dataset is a dataset for human body, face and hand detection with ~15k images. It contains ~106k different annotations, with multiple annotations per image.
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This dataset can be found on HuggingFace: https://huggingface.co/datasets/Short-Answer-Feedback/saf_communication_networks_english https://huggingface.co/datasets/Short-Answer-Feedback/saf_micro_job_german
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…The dataset is collected from the Internet, resulting in unconstrained face images similar to real world settings.
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The ACNE04 dataset includes 3756 Chinese face images with Acne. The ACNE04 dataset includes the annotations of local lesion numbers and global acne severity based on Hayashi Criterion.
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Dataset for face anti-spoofing in terms of both subjects and modalities. Specifically, it consists of subjects with videos and each sample has modalities (i.e., RGB, Depth and IR).
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…Conversation with Bing, 3/19/2024 (1) ShareGPT4V: Improving Large Multi-Modal Models with Better Captions. https://arxiv.org/pdf/2311.12793.pdf. (2) openchat/openchat_sharegpt4_dataset · Datasets at Hugging Face . https://huggingface.co/datasets/openchat/openchat_sharegpt4_dataset. (3) openchat/openchat_sharegpt_v3 · Datasets at Hugging Face. https://huggingface.co/datasets/openchat/openchat_sharegpt_v3. (4) RyokoAI /ShareGPT52K · Datasets at Hugging Face. https://huggingface.co/datasets/RyokoAI/ShareGPT52K.
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Open-Platypus is a family of fine-tuned and merged Large Language Models (LLMs) that achieves the strongest performance and currently stands at first place in HuggingFace's Open LLM Leaderboard.
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…Face-to-face communication networks : networks of face-to-face (non-online) interactions Graph classification datasets : disjoint graphs from different classes
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Although deep face recognition has achieved impressive results in recent years, there is increasing controversy regarding racial and gender bias of the models, questioning their trustworthiness and deployment We also propose a benchmark of experiments using DemogPairs over state-of-the-art deep face recognition models in order to analyze their cross-demographic behavior and potential demographic biases (see
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The MFA (Many Faces of Anger) dataset includes 200 in-the-wild videos from North American and Persian cultures with fine-grained labels of: 'annoyed', 'anger', 'disgust', 'hatred' and 'furious' and 13
The color FERET database is a dataset for face recognition. It contains 11,338 color images of size 512×768 pixels captured in a semi-controlled environment with 13 different poses from 994 subjects.
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The largest and cleanest face recognition dataset Glint360K, which contains 17,091,657 images of 360,232 individuals, baseline models trained on Glint360K can easily achieve state-of-the-art performance
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The Extended Yale B database contains 2414 frontal-face images with size 192×168 over 38 subjects and about 64 images per subject.
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The Oulu-NPU face presentation attack detection database consists of 4950 real access and attack videos. The 2D face artefacts were created using two printers and two display devices. The videos of the 55 subjects are divided into three subject-disjoint subsets for training, development and testing. Four test protocols are used to evaluate the generalization capability of face PAD methods across three covariates: unknown environmental conditions (namely illumination and background scene), acquisition
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…Being then not only the pioneer of talking about the importance of balanced datasets for learning and vision but also for being the first GAN augmented dataset of faces. The original description goes as follows: A bias-free dataset, containing human faces from different ethnical groups in a wide variety of illumination conditions and image resolutions. C&Z is enhanced with HDCGAN synthetic images, thus being the first GAN augmented dataset of faces.
Large Age-Gap (LAG) is a dataset for face verification, The dataset contains 3,828 images of 1,010 celebrities. For each identity at least one child/young image and one adult/old image are present.
DeeperForensics-1.0 represents the largest face forgery detection dataset by far, with 60,000 videos constituted by a total of 17.6 million frames, 10 times larger than existing datasets of the same kind The source videos are collected on 100 paid and consented actors from 26 countries, and the manipulated videos are generated by a newly proposed many-to-many end-to-end face swapping method, DF-VAE. 7
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P3M-10k contains 10421 high-resolution real-world face-blurred portrait images, along with their manually labeled alpha mattes.
CelebV-Text comprises 70,000 in-the-wild face video clips with diverse visual content, each paired with 20 texts generated using the proposed semi-automatic text generation strategy.
The MS-Celeb-1M dataset is a large-scale face recognition dataset consists of 100K identities, and each identity has about 100 facial images.
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FGNet is a dataset for age estimation and face recognition across ages. It is composed of a total of 1,002 images of 82 people with age range from 0 to 69 and an age gap up to 45 years
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…If you're curious to explore more, you can find the dataset on Hugging Face¹ or visit the official Parti website². Source: Conversation with Bing, 3/18/2024 (1) nateraw/parti-prompts · Datasets at Hugging Face. https://huggingface.co/datasets/nateraw/parti-prompts. (2) Parti: Pathways Autoregressive Text-to-Image Model
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FERG is a database of cartoon characters with annotated facial expressions containing 55,769 annotated face images of six characters.
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Halpe-FullBody is a full body keypoints dataset where each person has annotated 136 keypoints, including 20 for body, 6 for feet, 42 for hands and 68 for face.
The Wider Facial Landmarks in the Wild or WFLW database contains 10000 faces (7500 for training and 2500 for testing) with 98 annotated landmarks.
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SKSF-A contains 134 identities and corresponding sketches, making a total of 938 face-sketch pairs.
…If you're interested in specific tasks related to this dataset, there are also related datasets for news summarization and image captioning available on platforms like Hugging Face and Hugging Face²³. (1) GitHub - alexandrainst/NordjyllandNews: Dataset containing news from .... https://github.com/alexandrainst/NordjyllandNews. (2) alexandrainst/nordjylland-news-summarization · Datasets at Hugging Face . https://huggingface.co/datasets/alexandrainst/nordjylland-news-summarization. (3) Dataset Card for "nordjylland-news-image-captioning" - Hugging Face. https://huggingface.co/datasets/alexandrainst/nordjylland-news-image-captioning
…These patterns highlight the challenges these systems face in answering straightforward questions, often leading to incorrect responses and hallucinated explanations.
…All the caricatures and face images were collected from the Web.
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