Patent ID: 11869212
Assignee: DEEPING SOURCE INC.
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 0:
1. A method of training a video object detection model by using a training dataset, comprising steps of:
(a) in response to acquiring a training image from the training dataset, a learning device (i) inputting the training image and first prior information, set as having each of probabilities of each of objects existing in each of locations in the training image, into the video object detection model, to thereby instruct the video object detection model to detect the objects from the training image by referring to the first prior information and thus output first object detection information, and (ii) generating second prior information, which includes location information of the objects on the training image, by using the first object detection information;
(b) the learning device inputting the training image and the second prior information into the video object detection model, to thereby instruct the video object detection model to detect the objects on the training image by referring to the second prior information and thus output second object detection information; and
(c) the learning device generating at least one loss by referring to the second object detection information and a ground truth corresponding to the training image, to thereby train the video object detection model to minimize the loss,
wherein, at the step of (a), the learning device generates, as the second prior information, (i) a first mask having a same size as the training image or (ii) at least one second mask having a same size as at least one feature map obtained through a forward-propagation of the training image in the video object detection model, by using multiple pieces of location information of each of bounding boxes corresponding to each of the objects included in the first object detection information, wherein the first mask and the second mask are obtained by distinguishing each of regions corresponding to each of the bounding boxes from regions corresponding to non-bounding boxes.