-
1.
公开(公告)号:US20190306526A1
公开(公告)日:2019-10-03
申请号:US16374601
申请日:2019-04-03
Inventor: Seung-Hyun CHO , Je-Won KANG , Na-Young KIM , Jung-Kyung LEE , Joo-Young LEE , Hyunsuk KO , Youn-Hee KIM , Jong-Ho KIM , Jin-Wuk SEOK , Dae-Yeol LEE , Woong LIM , Se-Yoon JEONG , Hui-Yong KIM , Jin-Soo CHOI
IPC: H04N19/513 , H04N19/105 , H04N19/132 , G06N20/00
Abstract: Disclosed herein are an inter-prediction method and apparatus using a reference frame generated based on deep learning. In the inter-prediction method and apparatus, a reference frame is selected, and a virtual reference frame is generated based on the selected reference frame. A reference picture list is configured to include the generated virtual reference frame, and inter prediction for a target block is performed based on the virtual reference frame. The virtual reference frame may be generated based on a deep-learning network architecture, and may be generated based on video interpolation and/or video extrapolation that use the selected reference frame.
-
公开(公告)号:US20190246102A1
公开(公告)日:2019-08-08
申请号:US16270468
申请日:2019-02-07
Inventor: Seung-Hyun CHO , Youn-Hee KIM , Jin-Wuk SEOK , Joo-Young LEE , Woong LIM , Jong-Ho KIM , Dae-Yeol LEE , Se-Yoon JEONG , Hui-Yong KIM , Jin-Soo CHOI , Je-Won KANG , Na-Young KIM
IPC: H04N19/109 , G06N3/04 , H04N19/184 , H04N19/172 , H04N19/176
CPC classification number: H04N19/109 , G06N3/0454 , H04N19/172 , H04N19/176 , H04N19/184
Abstract: Disclosed herein are a video decoding method and apparatus and a video encoding method and apparatus. A virtual frame is generated by a video generation network including a generation encoder and a generation decoder. The virtual frame is used as a reference frame in inter prediction for a target. Further, a video generation network for inter prediction may be selected from among multiple video generation networks, and inter prediction that uses the selected video generation network may be performed.
-
3.
公开(公告)号:US20230297833A1
公开(公告)日:2023-09-21
申请号:US18306075
申请日:2023-04-24
Inventor: Seung-Hyun CHO , Youn-Hee KIM , Jin-Wuk SEOK , Joo-Young LEE , Woong LIM , Jong-Ho KIM , Dae-Yeol LEE , Se-Yoon JEONG , Hui-Yong KIM , Jin-Soo CHOI , Je-Won KANG
IPC: G06N3/08 , G06N3/04 , G06V10/82 , G06F18/214
CPC classification number: G06N3/08 , G06F18/214 , G06N3/04 , G06V10/82
Abstract: Disclosed herein are a method and apparatus for compressing learning parameters for training of a deep-learning model and transmitting the compressed parameters in a distributed processing environment. Multiple electronic devices in the distributed processing system perform training of a neural network. By performing training, parameters are updated. The electronic device may share the updated parameter thereof with additional electronic devices. In order to efficiently share the parameter, the residual of the parameter is provided to the additional electronic devices. When the residual of the parameter is provided, the additional electronic devices update the parameter using the residual of the parameter.
-
-