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Open Datasets for Academic Research

Nexdata has launched the AI Data-assisted Research Program for non-commercial organizations worldwide, including universities and academic institutions. This program provides valuable training datasets in computer vision, speech recognition, and other fields to support AI academic research.

Computer vision Computer vision
Speech Recognition Speech Recognition
Dataset Name Product type Capture Content Data Size Use of Data
1,000 people, Multiple Races,7 types of facial emotion recognition data Image Each person has seven expressions collected: normal, happy, surprised, sad, angry, disgusted, and fearful. 1,000 people Facial expression recognition
3,000 Images-Human Face Segmentation Data Image Segmentation annotation of human face, facial features,body and 3,000 images Face segmentation
3,000 Images of 106 Facial Landmarks Annotation Data (complex scenarios) Image 9 facial attributes and 106 facial landmarks 9 facial attributes: including gender, age, race, wearing cap/hat or not, wearing glasses or not, background, face orientation, eye status, mouth status 3,000 images Facial landmark location Face recognition
100 People-Driver Behavior Collection Data Image Dangerous driving behavior, fatigue driving behavior, visual movement behavior 100 people Driver behavior Detection
100 People-Liveness Detection Data Image Living body action video, lip language video, Non-living body video (anti-spoofing sample), Anti-spoofing data of lip language, Anti-spoofing data of RGB images 100 people liveness detection
50,016 Gesture Recognition Data Image 18 static hand gestures and 21 keypoints of the hand landmarks 50,016 data Gesture recognition
100 People-Human Face Recognition Data in Surveillance Image Human facial information in surveillance. The labels of gender and age were annotated. 100 people Face recognition
1,000 people, 7,156 Cross-age Face Images data Image The age spans are 10 years, and 4 images of each person in different ages were collected at least. 1,000 people Face recognition
1,000 People multi-race and Multi-pose Face Images Data Image Image quantity: 29 images per person (14 multi-pose face images of indoor scenes + 14 multi- pose face images of outdoor scenes + 1 ID photo) The labels of race, gender, age and face pose were annotated. 1,000 people Face recognition
10 Categories-200 Groups of Refined Urban Management Data Image 18 subcategories such as streets, snack streets, shop entrance, corridor, community entrance, construction sites, etc., and each group of data contains 2 images from different angles 200 groups Refined urban management
3,000 images Natural Scene OCR Data of 12 Languages Image Include Asian language family, European language family, and row-level quadrilateral bounding box annotation and transcription for the texts 3,000 images Multilingual OCR task
100 People with Occlusion and Multi-pose Face Recognition Data Image There're 200 images includes 4 kinds of light conditions * 10 kinds of occlusion cases (including non-occluded case) * 5 kinds of face pose. For each image, the labels of face pose and occlusion were annotated. 100 people Face recognition
100 People- 3D Liveness Detection Data Image Living face image data, anti-spoofing data of living face image and anti-spoofing data of mask image of three races with different skin color. Each image corresponds to a depth image, a depth information file, a camera internal parameters file 100 people Face recognition liveness detection
100 People- Electric Bicycle Entering Elevator Data Image For each subject, 1 images and 4 videos were collected and the gender, race and age should be labeled. For each video, the labels of collecting scene and electric bicycle model were annotated. 100 people Refined urban management
1,435 Images- Alpha Matte Human Body Segmentation Data( fine version) Image Collecting half body or full body images, and alpha matte segmentation annotation was done to the collecting human body. Label the subject’s race, gender, age, collecting scene. 1435 images Semantic Segmentation
200 People- Gait Recognition Data in Surveillance Image Each subject walked in slow speed, normal speed and fast speed according to the specified walking route. Each subject should walk 9 times with 3 seasonal clothes( summer, autumn and winner) respectively. 200 People Gait recognition
200 People- Re-ID Data in Real Surveillance Scenes Image Collect 8 kinds of human body orientation, and add bounding boxes and 15 attributes to human body. 200 people Re-ID
200 People- Re-ID Data in Surveillance Image Add bounding boxes and 15 attributes to human body. The gender, age, race, collecting scene, category of clothes, camera number, and camera height of subject should be labeled. 200 people Re-ID
200 Yellow People - Multi-Pose Face Images & Videos Data Image Face pose, head pose, nationality, gender, collecting environment and age 200 people Face recognition
Dataset Name Product type Collection equipment Data Size Use of Data
110 Hours- 11 Languages Conversational Speech Data by Telephone Speech Telephone 110 hours Speech recognition Voiceprint Recognition Machine translation
2.5 Hours- 5 Languages Speech Synthesis Corpus Speech Microphone 2.5 hours Speech synthesis
40 Hours- 4 Languages Children Reading Speech Data Speech Mobile phone 40 hours Speech recognition Voiceprint Recognition
1505 hours- Mandarin Speech Data by Mobile phone Speech Mobile phone 1505 hours, 6,278 speakers Speech recognition Voiceprint Recognition Machine translation
300 hours- Mandarin Conversational Speech Data by Mobile phone Speech Mobile phone 300 hours, 440 speakers Speech recognition Voiceprint Recognition Machine translation
200 Hours- Chinese Children Speech Data by Mobile phone Speech Mobile phone 200 hours, 557 speakers Speech recognition Voiceprint Recognition
200 hours- Mixed Speech with Chinese and English Data by Mobile phone Speech Mobile phone 200 hours, 701 speakers Speech recognition Voiceprint Recognition
300 Hours, 10 Chinese Dialects Speech Data by Mobile phone Speech Mobile phone 300 hours Speech recognition Dialect recognition
Interspeech_ Accented English Speech Recognition Competition Data Speech Mobile phone 200 hours, 528 speakers Speech recognition Language recognition
50 People- Far-field Speech Data in Home Environment Speech microphone array 50 speakers Speech enhancement Speech recognition
200 Hours- 10 Foreign Languages Speech Data by Mobile phoneSpeechMobile phone200 hoursAcoustic study
Language model training
Algorithm research
Note: Please apply for datasets reasonably according to the research field. The maximum number of applications for Computer Vision datasets is 6 sets.
Note: Please apply for datasets reasonably according to the research field. The maximum number of applications for speech recognition datasets is 4 sets.

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