CV

This dataset collects live attack video data of Chinese people. The collection scenarios cover indoor and outdoor environments and various light conditions. The shooting distance will be dynamically adjusted according to the actual shooting situation, mainly changing between full-body shots and head-and-shoulder shots. The types of attack methods collected include static attacks and dynamic attacks, totaling 7 categories. Static attack forms include photos, A4 color prints, and black-and-white prints. Dynamic attack forms include playing videos on iPads, Android phones, iPhones, and laptops. Each person will shoot 6 live videos and 22 attack videos in a normal and natural state, with each video lasting approximately 15 seconds. The collection tools are collected using a handheld method.

This dataset was collected using a 3D scanning device, which captured the facial and limb movements of the model wearing multiple pieces of clothing in an indoor setting. The 3D data was annotated with 57 key points for the face and 62 key points for the limbs. The collection was conducted using a 3D scanner, with each person completing the designated movements indoors. Each person was photographed and scanned in 16 postures, including 2 standard T-pose postures (tight clothing and personal attire). There were 62 key points for the human body and 57 key points for the face. The age range covered 7 to 60 years old, with a relatively balanced gender ratio, and the fluctuation was within 10%.

This dataset was collected in the XR perspective (first-person perspective) and contains 3D hand joint point data (21 points). It consists of two parts: static gestures and dynamic gestures. Both types of gestures include the left and right hands, totaling 22 different gestures. Moreover, the collection covers hands of different sizes.

The data collection equipment for this dataset is a 3D space scanning device. It was collected in Chinese supermarkets. Using a 3D space scanning camera device, 10 complete 3D scene data of medium and small-sized supermarkets were collected, and a 3D point cloud data model was generated for each supermarket.

This dataset contains facial image data. It includes three different skin colors: dark, light, and others (excluding fair). All the subjects in the collection are adults, with an equal male-to-female ratio. The image resolution is all above 1024×1024. This dataset covers common facial expressions, including natural expressions, happiness, excitement, etc. The facial angles mainly depict frontal views with the smallest deviation (yaw/pitch/roll all less than 30 degrees). The images are real, clear, without gray scale, and without watermarks.

This dataset is a collection and annotation library of multi-posture self-portrait pictures taken by Chinese people in natural scenes. Each collector has taken pictures in at least 4 different scenarios, including 3 indoor and 1 outdoor ones. Under different background environments, lighting conditions and distances, each collector completed 11 types of self-portraits while wearing glasses and without wearing glasses respectively. Each person took 100 pictures and 88 designated actions, as well as 12 actions that were freely performed by themselves. The collected portrait pictures were labeled with 21 key points.

The images of human figures in this dataset have been transformed into four different styles based on the original human images, including 3D cartoon, comic, watercolor painting, and sketch. There are four skin colors included: dark, fair, brown, and light. Each style-generated image contains all four skin colors.

This dataset collects video data of the personnel passing through the gate. The collection scenario is indoors and all the shooting is under normal lighting conditions. The installation of the cameras is based on the height and angle of the simulated gate passage. People are queued up for passage in groups of 1 to 3 (no backside data is collected). Each collector will take a frontal head-and-shoulders photo with a camera and record 12 random number audio clips with a mobile phone.

This dataset collects single-person photos/combined photos. The subjects are grouped into either single-person or 2-4 person combinations for shooting. The shooting scenes cover both indoor and outdoor environments, with various types of lighting. The subjects include various skin tones, face shapes, and eye shapes.