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1. 发明公开

US20240195971A1 IMAGE COMPRESSION AND DECODING, VIDEO COMPRESSION AND DECODING: METHODS AND SYSTEMS 审中-公开
公开(公告)号：US20240195971A1
公开(公告)日：2024-06-13
申请号：US18230361
申请日：2023-08-04
申请人： DEEP RENDER LTD
发明人： Chri BESENBRUCH , Ciro CURSIO , Christopher FINLAY , Vira KOSHKINA , Alexander LYTCHIER , Jan XU , Arsalan ZAFAR
IPC分类号： H04N19/126 , G06N3/045 , G06N3/084 , G06T3/4046 , G06T9/00 , G06V10/774 , H04N19/13
CPC分类号： H04N19/126 , G06N3/045 , G06N3/084 , G06T3/4046 , G06T9/002 , G06V10/774 , H04N19/13
摘要： There is disclosed a computer-implemented method for lossy image or video compression, transmission and decoding, the method including the steps of: (i) receiving an input image at a first computer system; (ii) encoding the input image using a first trained neural network, using the first computer system, to produce a latent representation; (iii) quantizing the latent representation using the first computer system to produce a quantized latent; (iv) entropy encoding the quantized latent into a bitstream, using the first computer system; (v) transmitting the bitstream to a second computer system; (vi) the second computer system entropy decoding the bitstream to produce the quantized latent; (vii) the second computer system using a second trained neural network to produce an output image from the quantized latent, wherein the output image is an approximation of the input image. Related computer-implemented methods, systems, computer-implemented training methods and computer program products are disclosed.

2. 发明公开

US20240107022A1 IMAGE ENCODING AND DECODING, VIDEO ENCODING AND DECODING: METHODS, SYSTEMS AND TRAINING METHODS 审中-公开
公开(公告)号：US20240107022A1
公开(公告)日：2024-03-28
申请号：US18513581
申请日：2023-11-19
申请人： DEEP RENDER LTD
发明人： Chri BESENBRUCH , Aleksandar CHERGANSKI , Christopher FINLAY , Alexander LYTCHIER , Jonathan RAYNER , Tom RYDER , Jan XU , Arsalan ZAFAR
IPC分类号： H04N19/13 , G06V10/422 , H04N19/124 , H04N19/42
CPC分类号： H04N19/13 , G06V10/422 , H04N19/124 , H04N19/42
摘要： Lossy or lossless compression and transmission, comprising the steps of: (i) receiving an input image; (ii) encoding it to produce a y latent representation; (iii) encoding the y latent representation to produce a z hyperlatent representation; (iv) quantizing the z hyperlatent representation to produce a quantized z hyperlatent representation; (v) entropy encoding the quantized z hyperlatent representation into a first bitstream, (vi) processing the quantized z hyperlatent representation to obtain a location entropy parameter μy, an entropy scale parameter σy, and a context matrix Ay of the y latent representation; (vii) processing the y latent representation, the location entropy parameter py and the context matrix Ay, to obtain quantized latent residuals; (viii) entropy encoding the quantized latent residuals into a second bitstream; and (ix) transmitting the bitstreams.

3. 发明公开

US20240070925A1 METHOD AND DATA PROCESSING SYSTEM FOR LOSSY IMAGE OR VIDEO ENCODING, TRANSMISSION AND DECODING 审中-公开
公开(公告)号：US20240070925A1
公开(公告)日：2024-02-29
申请号：US18458473
申请日：2023-08-30
申请人： DEEP RENDER LTD
发明人： Chris FINLAY , Jonathan RAYNER , Jan XU , Christian BESENBRUCH , Arsalan ZAFAR , Sebastjan CIZEL , Vira KOSHKINA
IPC分类号： G06T9/00 , G06T3/40
CPC分类号： G06T9/002 , G06T3/4046
摘要： A method of training one or more neural networks, the one or more neural networks being for use in lossy image or video encoding, transmission and decoding, the method comprising steps including: receiving an input image at a first computer system; encoding the input image using a first neural network and decoding the latent representation using a second neural network to produce an output image; at least one of the plurality of layers of the first or second neural network comprises a transformation; and the method further comprises the steps of: evaluating a difference between the output image and the input image and evaluating a function based on an output of the transformation; updating the parameters of the first neural network and the second neural network based on the evaluated difference and the evaluated function; and repeating the above steps.

4. 发明申请

US20230082809A1 METHOD AND DATA PROCESSING SYSTEM FOR LOSSY IMAGE OR VIDEO ENCODING, TRANSMISSIONAND DECODING 有权
公开(公告)号：US20230082809A1
公开(公告)日：2023-03-16
申请号：US18055621
申请日：2022-11-15
申请人： DEEP RENDER LTD
发明人： Thomas RYDER , Alexander LYTCHIER , Vira KOSHKINA , Christian BESENBRUCH , Arsalan ZAFAR
IPC分类号： G06T9/00 , G06V10/25 , G06N3/04 , G06N3/08 , G06T3/40
摘要： A method for lossy image or video encoding, transmission and decoding, the method comprising the steps of: receiving an input image at a first computer system; encoding the input image using a first trained neural network to produce a latent representation; identifying one or more regions of the input image associated with high visual sensitivity; encoding the one or more regions of the input image associated with high visual sensitivity using a second trained neural network to produce one or more region latent representations; performing a quantization process on the latent representation and the one or more region latent representations; transmitting the result of the quantization process to a second computer system; decoding the result of the quantization process to produce an output image, wherein the output image is an approximation of the input image.

5. 发明授权

US11544881B1 Method and data processing system for lossy image or video encoding, transmission and decoding 有权
公开(公告)号：US11544881B1
公开(公告)日：2023-01-03
申请号：US17748468
申请日：2022-05-19
申请人： DEEP RENDER LTD
发明人： Chris Finlay , Jonathan Rayner , Chri Besenbruch , Arsalan Zafar
IPC分类号： G06K9/46 , G06T9/00 , G06N3/08 , G06N3/04 , G06T3/40
摘要： A method for lossy image or video encoding, transmission and decoding, the method comprising the steps of: receiving an input image at a first computer system; encoding the first input training image using a first trained neural network to produce a latent representation; performing a quantization process on the latent representation to produce a quantized latent; entropy encoding the quantized latent using a probability distribution, wherein the probability distribution is defined using a tensor network; transmitting the entropy encoded quantized latent to a second computer system; entropy decoding the entropy encoded quantized latent using the probability distribution to retrieve the quantized latent; and decoding the quantized latent using a second trained neural network to produce an output image, wherein the output image is an approximation of the input training image.

6. 发明申请

US20220215511A1 SYSTEM AND METHOD FOR LOSSY IMAGE AND VIDEO COMPRESSION AND/OR TRANSMISSION UTILIZING A METANETWORK OR NEURAL NETWORKS 有权
公开(公告)号：US20220215511A1
公开(公告)日：2022-07-07
申请号：US17607468
申请日：2020-04-29
申请人： DEEP RENDER LTD
发明人： Arsalan ZAFAR , Christian BESENBRUCH
IPC分类号： G06T5/00 , G06N3/04 , G06T3/40 , G06T5/20 , G06V10/82 , G06V10/774
摘要： A system and method for lossy image and video compression that utilizes a metanetwork to generate a set of hyperparameters necessary for an image encoding network to reconstruct the desired image from a given noise image, and for lossy image and video compression and transmission that utilizes a neural network as a function to map a known noise image to a desired or target image, allowing the transfer only of hyperparameters of the function instead of a compressed version of the image itself. This allows the recreation of a high-quality approximation of the desired image by any system receiving the hyperparameters, provided that the receiving system possesses the same noise image and a similar neural network. The amount of data required to transfer an image of a given quality is dramatically reduced versus existing image compression technology.

7. 发明授权

US12075053B2 Image compression and decoding, video compression and decoding: methods and systems 有权
公开(公告)号：US12075053B2
公开(公告)日：2024-08-27
申请号：US18230376
申请日：2023-08-04
申请人： DEEP RENDER LTD
发明人： Chri Besenbruch , Ciro Cursio , Christopher Finlay , Vira Koshkina , Alexander Lytchier , Jan Xu , Arsalan Zafar
IPC分类号： H04N19/126 , G06N3/045 , G06N3/084 , G06T3/4046 , G06T9/00 , G06V10/774 , H04N19/13
CPC分类号： H04N19/126 , G06N3/045 , G06N3/084 , G06T3/4046 , G06T9/002 , G06V10/774 , H04N19/13
摘要： There is disclosed a computer-implemented method for lossy image or video compression, transmission and decoding, the method including the steps of: (i) receiving an input image at a first computer system; (ii) encoding the input image using a first trained neural network, using the first computer system, to produce a latent representation; (iii) quantizing the latent representation using the first computer system to produce a quantized latent; (iv) entropy encoding the quantized latent into a bitstream, using the first computer system; (v) transmitting the bitstream to a second computer system; (vi) the second computer system entropy decoding the bitstream to produce the quantized latent; (vii) the second computer system using a second trained neural network to produce an output image from the quantized latent, wherein the output image is an approximation of the input image. Related computer-implemented methods, systems, computer-implemented training methods and computer program products are disclosed.

8. 发明授权

US12028525B2 Image compression and decoding, video compression and decoding: methods and systems 有权
公开(公告)号：US12028525B2
公开(公告)日：2024-07-02
申请号：US18230312
申请日：2023-08-04
申请人： DEEP RENDER LTD
发明人： Chri Besenbruch , Ciro Cursio , Christopher Finlay , Vira Koshkina , Alexander Lytchier , Jan Xu , Arsalan Zafar
IPC分类号： H04N19/126 , G06N3/045 , G06N3/084 , G06T3/4046 , G06T9/00 , G06V10/774 , H04N19/13
CPC分类号： H04N19/126 , G06N3/045 , G06N3/084 , G06T3/4046 , G06T9/002 , G06V10/774 , H04N19/13
摘要： There is disclosed a computer-implemented method for lossy image or video compression, transmission and decoding, the method including the steps of: (i) receiving an input image at a first computer system; (ii) encoding the input image using a first trained neural network, using the first computer system, to produce a latent representation; (iii) quantizing the latent representation using the first computer system to produce a quantized latent; (iv) entropy encoding the quantized latent into a bitstream, using the first computer system; (v) transmitting the bitstream to a second computer system; (vi) the second computer system entropy decoding the bitstream to produce the quantized latent; (vii) the second computer system using a second trained neural network to produce an output image from the quantized latent, wherein the output image is an approximation of the input image. Related computer-implemented methods, systems, computer-implemented training methods and computer program products are disclosed.

9. 发明授权

US12026924B1 Method and data processing system for lossy image or video encoding, transmission and decoding 有权
公开(公告)号：US12026924B1
公开(公告)日：2024-07-02
申请号：US18458556
申请日：2023-08-30
申请人： DEEP RENDER LTD
发明人： Aleksandar Cherganski , Chris Finlay , Christian Etmann , Arsalan Zafar
IPC分类号： G06T9/00
CPC分类号： G06T9/002
摘要： A method of training one or more neural networks, the one or more neural networks being for use in lossy image or video encoding, transmission and decoding, the method comprising the steps of: receiving an input image at a first computer system; encoding the input image using a first neural network to produce a latent representation; decoding the latent representation using a second neural network to produce an output image, wherein the output image is an approximation of the input image; evaluating a function based on a difference between the output image and the input image; updating the parameters of the first neural network and the second neural network based on the evaluated function; and repeating the above steps using a first set of input images to produce a first trained neural network and a second trained neural network; wherein the difference between the output image and the input image is determined based on the output of a neural network acting as a discriminator; the parameters of the neural network acting as a discriminator are additionally updated based on the evaluated function; and the parameters of the neural network acting as a discriminator are updated at a first learning rate; wherein, after at least one of the updates of the parameters of the neural network acting as a discriminator, the first learning rate is updated; and the update to the first learning rate is based on an error of the output of the neural network acting as a discriminator.

10. 发明授权

US12015776B2 Image compression and decoding, video compression and decoding: methods and systems 有权
公开(公告)号：US12015776B2
公开(公告)日：2024-06-18
申请号：US18230314
申请日：2023-08-04
申请人： DEEP RENDER LTD
发明人： Chri Besenbruch , Ciro Cursio , Christopher Finlay , Vira Koshkina , Alexander Lytchier , Jan Xu , Arsalan Zafar
IPC分类号： H04N19/126 , G06N3/045 , G06N3/084 , G06T3/4046 , G06T9/00 , G06V10/774 , H04N19/13
CPC分类号： H04N19/126 , G06N3/045 , G06N3/084 , G06T3/4046 , G06T9/002 , G06V10/774 , H04N19/13
摘要： A computer-implemented method for lossy image or video compression, transmission and decoding, the method including the steps of: (i) receiving an input image at a first computer system; (ii) encoding the input image using a first trained neural network, using the first computer system, to produce a latent representation; (iii) quantizing the latent representation using the first computer system to produce a quantized latent; (iv) entropy encoding the quantized latent into a bitstream, using the first computer system; (v) transmitting the bitstream to a second computer system; (vi) the second computer system entropy decoding the bitstream to produce the quantized latent; (vii) the second computer system using a second trained neural network to produce an output image from the quantized latent, wherein the output image is an approximation of the input image. Related computer-implemented methods, systems, computer-implemented training methods and computer program products.

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