Beijing Jingdong Shangke Information Technology Co., Ltd.

Jd.com American Technologies Corporation

Jingdong Technology Holding Co., Ltd.

Jingdong Digits Technology Holding Co., Ltd.

Jd Finance America Corporation

Chinabank Payment (beijing) Technology Co., Ltd.

Liefeng Bo

Si Luo

Yue Zhang

Xinyao Wang

Longyin Wen

Guanghan Ning

Harry Huang

Lei Yi

Shiwen Shen

Guang Chen

A system and a method for object detection using augmented training dataset. The system includes a computing device, which is configured to: provide a two-dimensional (2D) image, extract feature vectors and estimate depths of 2D image pixels, generate a point cloud using the feature vectors and the depths, and project the point cloud using a new camera pose to obtain a projected image. The 2D image has a bounding box enclosing an object and labeled with the object. Each pixel within the bounding box is named bounding box pixel, each point in the point cloud corresponding to the bounding box pixel is named bounding box point, each image pixel in the projected image corresponding to the bounding box point is named projected bounding box pixel, and a projected bounding box is defined using the projected bounding box pixels and labeled with the object.

Data augmentation for object detection via differential neural rendering

A method and a system for detecting rough handling. The system has a camera and a computing device. The computing device is configured to: receive a video stream captured by the camera; detect persons and packages from video frames of the video stream; construct person and package trajectories based on the detected persons and packages; recognize an action between one person trajectory and one package trajectory, where the action includes the one person picks up, holds, and drops off the one package; and determine existence of a rough handling when, within a predetermined frames after drop-off of the one package, a motion distance of the one package is greater than a threshold distance, and a motion speed of the one package is greater than a threshold speed.

System and method for rough handling recognition in a distribution center via a robust visual solution

A method and a system for counting pigs in a pig house. The system includes a computing device and an imaging device. The computing device has a processor and a storage device storing computer executable code. The computer executable code is configured to: receive images captured from one end to the other end of the house; detect keypoints in the images using a neural network; identify pig skeletons by associating several related keypoints; track the skeletons in the images to obtain trajectories; divide each image into an activated zone and a deactivated zone; designate a spatial value of 0 for the skeletons in the activated zone and a spatial value of 1 for the skeletons in the deactivated zone; summating first order difference of the spatial values for each trajectory to obtain a trajectory count; and add the trajectory counts to obtain pig count.

System and method for video-based pig counting in the crowd

A method and a system for self-checkout. The system includes a scanner, an imaging device, and a computing device. The computing device is configured to: initiate a self-checkout event; instruct the imaging device to capture video frames of a region of interest (ROI); track the product; record scanning status and location status of the product; in response to receive a scanning signal from the scanner, record scanning status of the product as scanned; calculate a shoplifting risk score based on a number of the product having the scanning status of unscanned and disappears from the table region or ROI; and provide a shoplifting warning when the shoplifting score is large.

System and method for anti-shoplifting in self-checkout

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Liefeng Bo