Tailored Data Service for Retail

Nexdata supports object image and 2D/3D face anti-spoofing data collection as well as cross-camera tracking data collection by simulating real-world scenarios. We have extensive data service experience in face recognition, object detection, semantic segmentation, and target behavior recognition.

Face Recognition

Support 2D&3D face recognition and anti-spoofing data collection. Provide data labeling of bounding box, keypoints, segmentation etc.

Human Behavior Recognition

Support multi-device, multi-scene, multi-angle human behavior data collection/labeling for human locations, behaviors and attributes.

Store Traffic Counting

Support data collection of people flow data in a wide range of monitoring scenarios and data annotation of people distribution.

Search Relevance

Support data labeling of bounding boxes, segmentation, classification for objects in image.

Virtual Try-on

Support data collection of clothing and accessories, and provide data labeling of classification, segmentation and attribute.

Inventory Management

Supports data collection of warehouse and logistics environment, and provide data collection of classification, segmentation and attribute.

Compliance & Security

Nexdata place the utmost emphasis on data security and client trust. We follows Personal Information Protection Act, GDPR, CCPA, PIPC and HIPAA regulations. we have also achieved ISO 27001,ISO 27701 and ISO 9001 qualifications for security and regulatory compliance. Nexdata delivers unparalleled data security, earning the trust of our clients through our adherence to these globally recognized standards.

Case Studies

USE CASE：Facial Recognition Payment.
CHALLENGE：Clients need to improve the accuracy of face recognition on the payment platform and have high requirements on face data type and environmental lighting.
SOLUTION：Nexdata collected 2D/3D face data and face anti-spoofing data under different lighting, angles, occlusion, and perfromed keypoint annotation and facial feature annotation for collected data.

Automatic Identification of Unmanned Vending Machine

USE CASE：Automatic Identification of Unmanned Vending Machine.
CHALLENGE：Client wants to further enhance the automatic identification of the merchandise in the unmanned containers.
SOLUTION：Nexdata simulates the real scene by installing a camera in the unmanned container and collects 300,000 pictures. Due to the high difficulty of manual judgement on a wide range of goods, the labeling efficiency and accuracy rate were greatly improved by searching for labels and displaying multi-angle picture samples for each category of labels.

USE CASE：Virtual Clothes Fitting System.
CHALLENGE：Clients hopes to improve the recognition accuracy of the smart fitting system and has very high requirements for the accuracy of fashion segmentation. It needs to segment and label a large amount of character and clothing data and add attributes.
SOLUTION：Nexdata's refined matting template, with polygon and object fit within 3px, completely meets the customer's requirements for annotation precision and accuracy.

USE CASE：E-commerce OCR System.
CHALLENGE：The customer needed an OCR model to identify key information on product images. There are 5 languages in the pictures that need to be annotated, and there are blur, large-area occlusion, tilted text, etc. The annotation accuracy rate is required to reach 95%.
SOLUTION：Nexdata completed the data annotation of 15,000 OCR images within the specified time, with an accuracy rate of 98%.

Why Nexdata