[{"@type":"PropertyValue","name":"Data type","value":"sensor output data synthesized through 3D scene modeling with high similarity to the real world, like camera images, videos and point clouds."},{"@type":"PropertyValue","name":"Data annotation","value":"camera parameters, object classification/detection/segmentation, temporal/illumination/weather metadata, and human poses (head/eye/arm/leg positions and orientations)."},{"@type":"PropertyValue","name":"Application scenarios","value":"environmental modeling and data synthesis in autonomous driving and robotics."}]
{"id":1843,"datatype":"1","titleimg":"https://storage-product.datatang.com/damp/product/dataExampleImg/20250707162412/BPY250616001_demo.png?Expires=4102415999&OSSAccessKeyId=LTAI5tEBeSWUJiqjXvBMsxEu&Signature=njVnxYQezgHR2cs7hDM0MiukHfQ%3D","type1":"147","type1str":null,"type2":"151","type2str":null,"dataname":"3D Synthetic Sensor Dataset for DMS – Images, Video & Point Clouds","datazy":[{"title":"Data type","content":"sensor output data synthesized through 3D scene modeling with high similarity to the real world, like camera images, videos and point clouds.","desc":"Data type"},{"title":"Data annotation","content":"camera parameters, object classification/detection/segmentation, temporal/illumination/weather metadata, and human poses (head/eye/arm/leg positions and orientations).","desc":"Data annotation"},{"title":"Application scenarios","content":"environmental modeling and data synthesis in autonomous driving and robotics.","desc":"Application scenarios"}],"datatag":"synthetic data,ADS,in-cabin monitoring","technologydoc":null,"downurl":null,"datainfo":null,"standard":null,"dataylurl":null,"flag":null,"publishtime":null,"createby":null,"createtime":null,"ext1":null,"samplestoreloc":null,"hosturl":null,"datasize":null,"industryPlan":null,"keyInformation":"","samplePresentation":[{"name":"0_0.png","url":"https://storage-product.datatang.com/damp/product/dataExampleImg/20250707162412/0_0.png?Expires=4102415999&OSSAccessKeyId=LTAI5tEBeSWUJiqjXvBMsxEu&Signature=4YWI8FW9fxpYg2NkJE0IEUS%2Fw0s%3D","intro":"","size":5508136,"progress":100,"type":"jpg"},{"name":"0_19.png","url":"https://storage-product.datatang.com/damp/product/dataExampleImg/20250707162412/0_19.png?Expires=4102415999&OSSAccessKeyId=LTAI5tEBeSWUJiqjXvBMsxEu&Signature=18wSEJFfOuCVuk%2B0HHREDagppZE%3D","intro":"","size":5513087,"progress":100,"type":"jpg"},{"name":"0_20.png","url":"https://storage-product.datatang.com/damp/product/dataExampleImg/20250707162412/0_20.png?Expires=4102415999&OSSAccessKeyId=LTAI5tEBeSWUJiqjXvBMsxEu&Signature=0tcUTMH1qxvtUNEsz%2Fy6sQziBq8%3D","intro":"","size":5512304,"progress":100,"type":"jpg"}],"officialSummary":"This 3D high-fidelity synthetic dataset simulates real-world Driver Monitoring System (DMS) environments using photorealistic 3D scene modeling. It includes multi-modal sensor outputs such as camera images, videos, and point clouds, all generated through simulation. The dataset is richly annotated with object classification, detection, and segmentation labels, as well as human pose data (head, eye, arm, and leg position/orientation), camera parameters, and temporal metadata such as illumination and weather conditions. Ideal for training and evaluating models in autonomous driving, robotics, driver monitoring, computer vision, and synthetic perception tasks.","dataexampl":null,"datakeyword":["3D synthetic data","driver monitoring synthetic dataset","autonomous driving synthetic data","high-fidelity simulation dataset","synthetic point cloud data","camera simulation dataset","human pose synthetic dataset","synthetic lidar dataset","3D environment modeling","robotics synthetic data","DMS dataset"],"isDelete":null,"ids":null,"idsList":null,"datasetCode":null,"productStatus":null,"tagTypeEn":"Task Type,Modalities","tagTypeZh":null,"website":null,"samplePresentationList":null,"datazyList":null,"keyInformationList":null,"dataexamplList":null,"bgimg":null,"datazyScriptList":null,"datakeywordListString":null,"sourceShowPage":"computer","BGimg":"","voiceBg":["/shujutang/static/image/comm/audio_bg.webp","/shujutang/static/image/comm/audio_bg2.webp","/shujutang/static/image/comm/audio_bg3.webp","/shujutang/static/image/comm/audio_bg4.webp","/shujutang/static/image/comm/audio_bg5.webp"],"firstList":[{"name":"0_29.png","url":"https://storage-product.datatang.com/damp/product/dataExampleImg/20250707162412/0_29.png?Expires=4102415999&OSSAccessKeyId=LTAI5tEBeSWUJiqjXvBMsxEu&Signature=MGK74gJ3sp1loicrwBm2M0dClaw%3D","intro":"","size":5514654,"progress":100,"type":"jpg"},{"name":"0_30.png","url":"https://storage-product.datatang.com/damp/product/dataExampleImg/20250707162412/0_30.png?Expires=4102415999&OSSAccessKeyId=LTAI5tEBeSWUJiqjXvBMsxEu&Signature=TaMUOaeShEA8QtrHnEqSs1CyYVs%3D","intro":"","size":5512925,"progress":100,"type":"jpg"}]}
3D Synthetic Sensor Dataset for DMS – Images, Video & Point Clouds
3D synthetic data
driver monitoring synthetic dataset
autonomous driving synthetic data
high-fidelity simulation dataset
synthetic point cloud data
camera simulation dataset
human pose synthetic dataset
synthetic lidar dataset
3D environment modeling
robotics synthetic data
DMS dataset
This 3D high-fidelity synthetic dataset simulates real-world Driver Monitoring System (DMS) environments using photorealistic 3D scene modeling. It includes multi-modal sensor outputs such as camera images, videos, and point clouds, all generated through simulation. The dataset is richly annotated with object classification, detection, and segmentation labels, as well as human pose data (head, eye, arm, and leg position/orientation), camera parameters, and temporal metadata such as illumination and weather conditions. Ideal for training and evaluating models in autonomous driving, robotics, driver monitoring, computer vision, and synthetic perception tasks.
This is a paid datasets for commercial use, research purpose and more. Licensed ready made datasets help jump-start AI projects.
Specifications
Data type
sensor output data synthesized through 3D scene modeling with high similarity to the real world, like camera images, videos and point clouds.
Data annotation
camera parameters, object classification/detection/segmentation, temporal/illumination/weather metadata, and human poses (head/eye/arm/leg positions and orientations).
Application scenarios
environmental modeling and data synthesis in autonomous driving and robotics.