Jvc Kenwood Corporation

Godo Kaisha IP Bridge 1

Victor Company of Japan, Limited

Jcv Kenwood Corporation

Hideki Takehara

Shigeru Fukushima

Hiroya Nakamura

Toru Kumakura

Satoru Sakazume

Hiroyuki Kurashige

Motoharu Ueda

Masayoshi Nishitani

Kazumi Arakage

Satoru Hirose

Tatsumi Naganuma

Akinori Suyama

Shingo Kida

Yincheng Yang

Takeshi Aoki

Hiroyuki Kumakura

Katsumi Tomizawa

Ryo Miyakuchi

Naribumi Omata

Ichiro Ando

Jeong-ju Choe

Yasushi Watanabe

Manamu Takahashi

Jeongju Choe

A memory consolidation controller includes: an acquisition unit configured to acquire brain activity information indicating a state of brain activity of a subject; a determination unit configured to determine a sleep level indicating a depth of sleep of the subject and determine an activity state in a predetermined region of the subject's brain based on the acquired brain activity information; and a reproduction control unit configured to cause a reproduction device to reproduce a content that stimulates an auditory sense of the subject based on a determination result of the determination unit.

Memory consolidation controller, memory consolidation method, and non-transitory storage medium

A picture coding device, for coding a moving picture using inter prediction based on inter prediction information in units of blocks into which each picture of moving pictures is divided and forming a bitstream, includes a coding information storage unit configured to add the inter prediction information used in the inter prediction to a history-based motion vector predictor candidate list, a spatial motion vector predictor candidate derivation unit configured to derive a spatial motion vector predictor candidate from a block neighboring a target block and add the spatial motion vector predictor candidate to a motion vector predictor candidate list, and a temporal motion vector predictor candidate derivation unit configured to derive a temporal motion vector predictor candidate from a block located at the same position as or near the target block and add the temporal motion vector predictor candidate to the motion vector predictor candidate list.

Picture coding device, picture coding method, and picture coding program, picture decoding device, picture decoding method, and picture decoding program

A far-infrared image acquisition unit acquires a far-infrared image. An image conversion unit converts the acquired far-infrared image into a visible light image. A visible light image trained model storage unit stores a first visible light image trained model having performed learning using the visible light image as training data. A transfer learning unit performs transfer learning on a first visible light image trained model by using the visible light image obtained by conversion as training data to generate a second visible light image trained model.

Machine learning device and far-infrared image capturing device

A picture decoding device includes a spatial candidate derivation unit configured to derive a spatial candidate from inter prediction information of a block neighboring a decoding target block and register the derived spatial candidate as a candidate to a first candidate list, a history-based candidate derivation unit configured to generate a second candidate list by adding a history-based candidate included in a history-based candidate list as a candidate to the first candidate list, a candidate selection unit configured to select a selection candidate from candidates included in the second candidate list, and an inter prediction unit configured to perform inter prediction using the selection candidate.

Picture decoding device, picture decoding method, and picture decoding program with history-based candidate selection

A picture coding device, for coding a moving picture using inter prediction based on inter prediction information in units of blocks and forming a bitstream, includes a coding information storage unit configured to store inter prediction information used in the inter prediction of a coded block in a history-based motion vector predictor candidate list, a spatial merging candidate derivation unit configured to derive a spatial merging candidate from inter prediction information of a block spatially neighboring a coding target block and to add the spatial merging candidate to a merging candidate list, and a history-based merging candidate derivation unit configured to derive a history-based merging candidate from the inter prediction information stored in the history-based motion vector predictor candidate list and to add the history-based merging candidate to the merging candidate list.

Picture coding device, picture coding method, and picture coding program, picture decoding device, picture decoding method and picture decoding program

A picture coding device includes: a block vector candidate derivation unit that derives block vector candidates of a target block in a target picture from coding information stored in coding information storage memory; a selector that selects a selected block vector from the block vector candidates; and a reference position correction unit that performs a correction regarding a reference block to be referred to by the selected block vector so that a reference position of the reference block is to be corrected to refer to an inside of a referenceable region, in which a decoded sample in the target picture is acquired from decoded picture memory as a prediction value of the target block based on the reference position of the reference block.

Moving picture coding device, moving picture coding method, moving picture coding program, moving picture decoding device, moving picture decoding method, and moving picture decoding program

A far-infrared image training data acquisition unit acquires a far-infrared image in a first predetermined time zone. A visible light image training data acquisition unit acquires a visible light image in a second predetermined time zone. A visible light image generation model training unit machine-learns the far-infrared image in the first predetermined time zone and the visible light image in the second predetermined time zone as training data by a generative adversarial network, and generates a trained generation model, which generates the visible light image in the second predetermined time zone from the far-infrared image in the first predetermined time zone. Through machine learning by a generative adversarial network, the visible light image generation model training unit further generates a trained identification model, which identifies whether or not the far-infrared image is a far-infrared image captured in the first predetermined time zone.

Machine learning device and image processing device

A merge candidate list is generated, a merge candidate is selected from the merge candidate list as a merge candidate, a bitstream is decoded to derive a motion vector difference, and a corrected merge candidate is derived by adding the motion vector difference to a motion vector of the selected merge candidate for a first prediction without scaling and subtracting the motion vector difference from a motion vector of the selected merge candidate for a second prediction without scaling.

Image decoding device, image decoding method, and image decoding program

A visible light image generation model learning unit generates a trained visible light image generation model that generates a visible light image in a second time zone from a far-infrared image in a first time zone. The visible light image generation model learning unit includes a first learning unit that machine-learns the far-infrared image in the first time zone and a far-infrared image in the second time zone as teacher data and generates a trained first generation model that generates the far-infrared image in the second time zone from the far-infrared image in the first time zone, and a second learning unit that machine-learns the far-infrared image in the second time zone and the visible light image in the second time zone as teacher data and generates a trained second generation model that generates the visible light image in the second time zone from the far-infrared image in the second time zone.

Machine learning device, image processing device, machine learning method, and machine learning program

There is provided a technique including: a merging candidate constructor structured to construct a merging candidate list including merging candidates having a maximum number of merging candidates including spatial merging candidates; a normal merging candidate selector structured to select a normal merging candidate that is uni-prediction or bi-prediction from the merging candidate list based on a merge index; and a triangle merging candidate selector structured to select a first triangle merging candidate that is uni-prediction from the merging candidate list based on a first triangle merge index and select a second triangle merging candidate that is uni-prediction based on a second triangle merge index, in which a first maximum number of triangle merging candidates regarding the first triangle merge index is the same as the maximum number of merging candidates.

Picture coding device, picture coding method, picture coding program, picture decoding device, picture decoding method, and picture decoding program

A picture coding device includes: a block vector candidate derivation unit that derives block vector candidates of a coding target block in a coding target picture from coding information stored in a coding information storage memory; a selector that selects a selected block vector from the block vector candidates; a storage that stores coded pictures of a predetermined number of intra block copy standard blocks immediately before the coding target block; and a reference region boundary correction unit that removes a coded picture of one intra block copy standard block in the storage from a referenceable region after completion of a coding process of the coding target block, and determines whether an upper left position and a lower right position of a reference block indicated by the selected block vector are both included in the referenceable region.

Coding/decoding video with reference boundary correction

In order to provide low-load, efficient coding technology, a moving-picture decoding device includes a spatial motion information candidate derivation unit configured to derive a spatial motion information candidate from motion information of a block neighboring a decoding target block in a space domain and a history-based motion information candidate derivation unit configured to derive a history-based motion information candidate from a memory where motion information of a decoded block is retained, wherein the history-based motion information candidate derivation unit preferentially derives old motion information without making a comparison of the motion information with the spatial motion information candidate.

Moving image encoding device, moving image encoding method, moving image encoding program, moving image decoding device, moving image decoding method, and moving image decoding program

A motion vector decoding unit derives a motion vector of a prediction block subject to decoding on the basis of a motion vector of a candidate block included in candidate blocks selected from neighboring blocks. The motion compensation prediction unit performs motion compensation prediction using the derived motion vector. In case a motion vector number of a first block and a motion vector number of a second block are identical with each other, the motion vector decoding unit determines whether or not to set the second block as a candidate block in accordance with whether or not a reference index indicating a reference picture that the motion vector of the first block refers to and a reference index indicating a reference picture that the motion vector of the second block refers to are identical with each other.

Moving picture decoding device, moving picture decoding method, and moving picture decoding program

There is provided a technique that includes a triangle merging candidate list constructor structured to construct a triangle merging candidate list including spatial merging candidates, a first triangle merging candidate selector structured to select, from the triangle merging candidate list, a first triangle merging candidate that is uni-prediction, and a second triangle merging candidate selector structured to select, from the triangle merging candidate list, a second triangle merging candidate that is uni-prediction, in which in a region where motion compensation by weighted averaging by the first triangle merging candidate and the second triangle merging candidate is performed, uni-prediction motion information of one of the first triangle merging candidate or the second triangle merging candidate is saved.

A prediction information deriving unit derives the inter-prediction information candidates from inter-prediction information of a prediction block neighboring to a coding target prediction block or a prediction block present at the same position as or near the coding target prediction block in a coded picture at a temporally different position from the coding target prediction block. A candidate supplementing unit supplements inter-prediction information candidates having the same prediction mode, reference index, and motion vector until the number of inter-prediction information candidates reaches the designated number of candidates when the number of inter-prediction information candidates is smaller than the designated number of candidates.

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Yokosuka, Japan

Hideki Takehara