Baidu USA LLC

Beijing Baidu Netcom Science and Technology Co., Ltd.

Yafeng Deng

Yi Yang

Errui Ding

Fuguo Zhu

Yinan Yu

Long Gong

Fujian Wang

Lichao Huang

The present disclosure provides a photo-taking prompting method and apparatus, an apparatus and a non-volatile computer storage medium. On the one hand, a user's image information is collected while the user finds view, then the user's face posture information is obtained from the image information, then face posture information of a preset photo-taking template is compared with the user's face posture information, and the user is prompted to adjust the face posture according to a comparison result. The technical solutions provided by embodiments of the present disclosure may implement prompting the user's face posture adjustment while the user finds view and thereby implement providing guidance for the user's face posture, and solve the problem in the prior art about failure to perform photo-taking guidance while the user finds view.

Photo-taking prompting method and apparatus, an apparatus and non-volatile computer storage medium

Presented are systems and methods that provide a unified end-to-end detection pipeline for object detection that achieves impressive performance in detecting very small and highly overlapped objects in face and car images. Various embodiments of the present disclosure provide for an accurate and efficient one-stage FCN-based object detector that may be optimized end-to-end during training. Certain embodiments train the object detector on a single scale using jitter-augmentation integrated landmark localization information through joint multi-task learning to improve the performance and accuracy of end-to-end object detection. Various embodiments apply hard negative mining techniques during training to bootstrap detection performance. The presented are systems and methods are highly suitable for situations where region proposal generation methods may fail, and they outperform many existing sliding window fashion FCN detection frameworks when detecting objects at small scales and under heavy occlusion conditions.

Systems and methods for end-to-end object detection

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Beijing, China

Yafeng Deng