Baidu Online Network Technology (Beijing) Co., Ltd.

Beijing Baidu Netcom Science Technology Co., Ltd

Beijing Baidu Netcom Science and Technology Co., Ltd.

Baidu Online Network Technology Co., Ltd.

Ting Yun

Guoqing Chen

Yuanhang Li

Tiansheng Deng

Chao Wang

Fei Li

Lin Wang

Yunfeng Liu

Peng Du

Yi Lv

Tianbao Yu

Yupeng Ning

Xiangming Zhao

Saiqun Lin

Zhanguo Chang

Miao Chen

Xiju Liao

Provided are a video editing method, an electronic device and a medium. The video editing method includes: acquiring a first video; cutting the first video to obtain a plurality of segments; determining a plurality of labels respectively corresponding to the plurality of segments, each label among the plurality of labels selected from one of a first label, a second label, a third label or a fourth label, where the first label indicates singing, where the second label indicates speaking, where the third label indicates background music, and where the fourth label indicates a segment that does not correspond to the first label, the second label or the third label; determining a singing segment set based on the plurality of labels, the singing segment set including consecutive segments among the plurality of segments that correspond to the first label; and generating a second video based on the singing segment set.

Video editing method and apparatus, electronic device and medium

A method of generating an image sample, which relates to a field of an artificial intelligence technology, in particular to fields of a deep learning technology and a computer vision technology. The method includes: generating a handwritten text image according to at least one handwritten sample image; and generating a target sample image with an annotation box according to the handwritten text image and a background image, where the annotation box is used to represent a region in which the handwritten text image is located in the background image. The present disclosure further provides a method of recognizing a text, an electronic device and a storage medium.

Method of generating image sample, method of recognizing text, device and medium

A method, apparatus, and electronic device for processing a video, a medium and a product are presented. An implementation of the method includes: acquiring a target video; selecting, from at least one preset model, a preset model as a target model; determining output data of the target model based on the target video and the target model; reselecting, in response to determining that the output data does not meet a condition corresponding to the target model, another preset model as the target model from the at least one preset model until the output data of the target model meets the condition corresponding to the target model; and determining, based on the output data, a dynamic cover from the target video.

Method and apparatus for processing video, electronic device, medium and product

Embodiments of the present disclosure provide a method and apparatus for generating a video. The method may include: acquiring a cartoon face image sequence of a target cartoon character from a received cartoon-style video, and generating a cartoon face contour figure sequence based on the cartoon face image sequence; generating a face image sequence for a real face based on the cartoon face contour figure sequence and a received initial face image of the real face, a face expression in the face image sequence matching a face expression in the cartoon face image sequence; generating a cartoon-style face image sequence for the real face according to the face image sequence; and replacing a face image of the target cartoon character in the cartoon-style video with a cartoon-style face image in a cartoon-style face image sequence, to generate a cartoon-style video corresponding to the real face.

Method and apparatus for generating video

The present disclosure provides a video jitter detection method and an apparatus. The video jitter detection method includes: acquiring a video; inputting the video into a detection model to obtain an evaluation value of the video, where the evaluation value is used to indicate a degree of jitter of the video; where the detection model is a model obtained by training using video samples in a video sample set as inputs and evaluation values of the video samples in the video sample set as outputs. By inputting the video to be detected into the detection model, the evaluation value of the video can be acquired through the detection model, thereby whether the video is jittery is determined, which realizes the video jitter detection end-to-end, and improves the detection accuracy and robustness of video jitter.

Video jitter detection method and apparatus

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Beijing, China

Ting Yun