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公开(公告)号：US20230058437A1
公开(公告)日：2023-02-23
申请号：US17706409
申请日：2022-03-28
Inventor： Zhen WU , Jiaxiang GE , Xiao WANG , Xianze SU , Bing LIU , Jiawei WANG , Dan WANG , Song YANG , Jinghao HAO , Yufang WU , Qin QU , Bingqi ZHANG , Xiaoyin FU , Siyuan WU , Chao LI , Cong GAO , Lei JIA
IPC: G10L15/22 , G10L15/34 , G10L13/027 , G06F40/40
Abstract: The present disclosure provides a method for a human-computer interaction, an apparatus for a human-computer interaction, a device, and a storage medium, and the present disclosure relates to the field of artificial intelligence, such as deep learning and voice. A specific implementation includes: acquiring a voice command; performing voice recognition on the voice command to determine a corresponding voice text; sending, in response to satisfying a preset information sending condition, the voice text to a cloud; receiving a resource for the voice command returned from the cloud; and responding to the voice command based on the resource.
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公开(公告)号：US20210201448A1
公开(公告)日：2021-07-01
申请号：US17203437
申请日：2021-03-16
Inventor： Chao LI , Dongliang HE , Fu LI , Hao SUN
Abstract: An image filling method and apparatus, a device and a storage medium are disclosed. The image filling method includes: performing multilevel encoding processing on features of an image to be filled to generate multilevel encoded feature layers, sizes of the multilevel encoded feature layers being reduced layer by layer; performing layer-by-layer decoding processing on the multilevel encoded feature layers to obtain multilevel decoded feature layers and a first image, there being no missing region in the first image, wherein the layer-by-layer decoding processing includes a concatenation operation on a decoded feature layer and an encoded feature layer with a same size; and performing up-sampling processing on the first image to obtain multilevel up-sampled feature layers and a second image optimized by the up-sampling processing, the up-sampling processing including a concatenation operation on an up-sampled feature layer and a decoded feature layer with a same size.
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3.发明申请公开(公告)号：US20200372609A1
公开(公告)日：2020-11-26
申请号：US16810986
申请日：2020-03-06
Inventor： Chao LI , Dongliang HE , Xiao LIU , Yukang DING , Shilei WEN , Errui DING , Henan ZHANG , Hao SUN
IPC: G06T3/40
Abstract: A super-resolution video reconstruction method, device, apparatus and a computer-readable storage medium are provided. The method includes: extracting a hypergraph from consecutive frames of an original video; inputting a hypergraph vector of the hypergraph into a residual convolutional neural network to obtain an output result of the residual convolutional neural network; and inputting the output result of the residual convolutional neural network into a spatial upsampling network to obtain a super-resolution frame, wherein a super-resolution video of the original video is formed by multiple super-resolution frames.
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公开(公告)号：US20200322684A1
公开(公告)日：2020-10-08
申请号：US16622876
申请日：2018-07-18
Inventor： Liqiang DONG , Xiaodong CAO , Xinwei YU , Guoqing CHEN , Chunxin JIA , Su WANG , Jinsheng CHEN , Xi ZENG , Xin ZHANG , Jiaqi JIANG , Zhenhua LIU , Yueyang SONG , Shilei WEN , Fu LI , Hao SUN , Xiao LIU , Lixing GONG , Tianbao YU , Feng LI , Fei LI , Junling ZHAO , Haiping WANG , Yan XIA , Chao LI , Xiu WEI , Qi GAO
IPC: H04N21/466 , H04N21/488 , H04N21/44 , H04N21/431 , G06F16/735 , G06F16/783
Abstract: The present disclosure provides a video recommendation method and a video recommendation apparatus, a computer device and a storage medium. The video recommendation method includes: acquiring a target short video; identifying, from candidate long videos, a target long video that the target short video is from based on a video fingerprint feature of the target short video and video fingerprint features of the candidate long videos; and recommending the target long video.
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公开(公告)号：US20220207299A1
公开(公告)日：2022-06-30
申请号：US17460646
申请日：2021-08-30
Inventor： Chao LI , Dongliang HE , Wenling GAO , Fu LI , Hao SUN
Abstract: A method for building an image enhancement model includes obtaining training data; building a neural network model consisting of a feature extraction module, at least one channel dilated convolution module and a spatial upsampling module, where each channel dilated convolution module includes a spatial downsampling submodule, a channel dilation submodule and a spatial upsampling submodule; training the neural network model by using the video frames and the standard images corresponding to the video frames until the neural network model converges, to obtain an image enhancement model. In addition, a method for image enhancement includes obtaining a video frame to be processed; taking the video frame to be processed as an input of an image enhancement model, and taking an output result of the image enhancement model as an image enhancement result of the video frame to be processed.
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Patent Agency Ranking
公开(公告)号：US20210407479A1
公开(公告)日：2021-12-30
申请号：US17474776
申请日：2021-09-14
Inventor： Siyuan WU , Chao LI , Chenxi SUN
IPC: G10H1/00 , G10H1/06 , G11B27/031
Abstract: The disclosure provides a method for synthesizing a song multimedia, an electronic device and a storage medium. Material obtaining modes are provided based on a song multimedia synthesis request. User audios provided by a user are obtained based on a selected material obtaining mode. A user timbre output by a timbre extraction model is obtained by inputting the user audios into the timbre extraction model. Lyrics to be synthesized and a tune to be synthesized provided by the user are obtained based on the selected material obtaining mode, and a synthesized song multimedia is obtained by inputting the user timbre, the lyrics to be synthesized and the tune to be synthesized into a song synthesis model.
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公开(公告)号：US20210329195A1
公开(公告)日：2021-10-21
申请号：US17361055
申请日：2021-06-28
Inventor： Chao LI
Abstract: The disclosure provides a method and an apparatus for interpolating a frame to a video. A first deep-level feature of a first frame is obtained and a second deep-level feature of a second frame is obtained. Forward optical flow information and inverse optical flow information between the first frame and the second frame are obtained based on first deep-level feature and the second deep-level feature. An interpolated frame between the first frame and the second frame is generated based on the forward optical flow information and the inverse optical flow information, and the interpolated frame is inserted between the first frame and the second frame.
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公开(公告)号：US20210360252A1
公开(公告)日：2021-11-18
申请号：US17125370
申请日：2020-12-17
Inventor： Chao LI , Yukang DING , Dongliang HE , Fu LI , Hao SUN , Shilei WEN , Hongwu ZHANG , Errui DING
IPC: H04N19/132 , H04N19/172 , G06N3/04 , G06K9/62
Abstract: A method for video frame interpolation, a related electronic device and a storage medium is disclosed. A video is obtained. An (i−1)th frame and an ith frame of the video are obtained. Visual semantic feature maps and depth maps of the (i−1)th frame and the ith frame are obtained. Frame interpolation information is obtained based on the visual semantic feature maps and the depth maps. An interpolated frame between the (i−1)th frame and the ith frame is generated based on the frame interpolation information and the (i−1)th frame and is inserted between the (i−1)th frame and the ith frame.
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公开(公告)号：US20210209731A1
公开(公告)日：2021-07-08
申请号：US17024253
申请日：2020-09-17
Inventor： Chao LI , Shilei WEN , Errui DING
Abstract: Embodiments of the present disclosure provide a video processing method, a video processing device and a related non-transitory computer readable storage medium. The method includes the following. Frame sequence data of a low-resolution video to be converted is obtained. Pixel tensors of each frame in the frame sequence data are inputted into a pre-trained neural network model to obtain high-resolution video frame sequence data corresponding to the video to be converted output by the neural network model. The neural network model obtains the high-resolution video frame sequence data based on high-order pixel information of each frame in the frame sequence data.
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公开(公告)号：US20200349389A1
公开(公告)日：2020-11-05
申请号：US16828845
申请日：2020-03-24
Inventor： Jiadong ZHANG , Chao LI , Guoyi LIU
Abstract: The present disclosure relates to a method and a device for training an image recognition model and a related device. The method includes: extracting sub-image feature data from a detection frame sub-image of an input image; determining element feature data matching the sub-image feature data from an index element database; and outputting images related to the element feature data as training images for training the image recognition model. The index element database is built in advance based on a plurality of element feature data extracted from a plurality of candidate images.
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