WO2018170393A3 - Frame interpolation via adaptive convolution and adaptive separable convolution - Google Patents

Frame interpolation via adaptive convolution and adaptive separable convolution Download PDF

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Publication number
WO2018170393A3
WO2018170393A3 PCT/US2018/022858 US2018022858W WO2018170393A3 WO 2018170393 A3 WO2018170393 A3 WO 2018170393A3 US 2018022858 W US2018022858 W US 2018022858W WO 2018170393 A3 WO2018170393 A3 WO 2018170393A3
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WO
WIPO (PCT)
Prior art keywords
convolution
pixel
frame
input
adaptive
Prior art date
Application number
PCT/US2018/022858
Other languages
French (fr)
Other versions
WO2018170393A2 (en
WO2018170393A9 (en
Inventor
Feng Liu
Simon NIKLAUS
Long MAI
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Portland State University
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Publication date
Application filed by Portland State University filed Critical Portland State University
Priority to US16/495,029 priority Critical patent/US11468318B2/en
Priority to KR1020197030137A priority patent/KR102474168B1/en
Publication of WO2018170393A2 publication Critical patent/WO2018170393A2/en
Publication of WO2018170393A9 publication Critical patent/WO2018170393A9/en
Publication of WO2018170393A3 publication Critical patent/WO2018170393A3/en

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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N7/00—Television systems
    • H04N7/01—Conversion of standards, e.g. involving analogue television standards or digital television standards processed at pixel level
    • H04N7/0127—Conversion of standards, e.g. involving analogue television standards or digital television standards processed at pixel level by changing the field or frame frequency of the incoming video signal, e.g. frame rate converter
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/08—Learning methods
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N20/00—Machine learning
    • G06N20/10—Machine learning using kernel methods, e.g. support vector machines [SVM]
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T3/00—Geometric image transformation in the plane of the image
    • G06T3/40—Scaling the whole image or part thereof
    • G06T3/4007—Interpolation-based scaling, e.g. bilinear interpolation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T3/00—Geometric image transformation in the plane of the image
    • G06T3/40—Scaling the whole image or part thereof
    • G06T3/4046—Scaling the whole image or part thereof using neural networks
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N7/00—Television systems
    • H04N7/01—Conversion of standards, e.g. involving analogue television standards or digital television standards processed at pixel level
    • H04N7/0135—Conversion of standards, e.g. involving analogue television standards or digital television standards processed at pixel level involving interpolation processes
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/50—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using predictive coding
    • H04N19/587—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using predictive coding involving temporal sub-sampling or interpolation, e.g. decimation or subsequent interpolation of pictures in a video sequence

Abstract

Systems, methods, and computer-readable media for context-aware synthesis for video frame interpolation are provided. A convolutional neural network (ConvNet) may, given two input video or image frames, interpolate a frame temporarily in the middle of the two input frames by combining motion estimation and pixel synthesis into a single step and formulating pixel interpolation as a local convolution over patches in the input images. The ConvNet may estimate a convolution kernel based on a first receptive field patch of a first input image frame and a second receptive field patch of a second input image frame. The ConvNet may then convolve the convolutional kernel over a first pixel patch of the first input image frame and a second pixel patch of the second input image frame to obtain color data of an output pixel of the interpolation frame. Other embodiments may be described and/or claimed.
PCT/US2018/022858 2017-03-17 2018-03-16 Frame interpolation via adaptive convolution and adaptive separable convolution WO2018170393A2 (en)

Priority Applications (2)

Application Number Priority Date Filing Date Title
US16/495,029 US11468318B2 (en) 2017-03-17 2018-03-16 Frame interpolation via adaptive convolution and adaptive separable convolution
KR1020197030137A KR102474168B1 (en) 2017-03-17 2018-03-16 Frame interpolation with adaptive convolution and adaptive disjoint convolution

Applications Claiming Priority (4)

Application Number Priority Date Filing Date Title
US201762473234P 2017-03-17 2017-03-17
US62/473,234 2017-03-17
US201762485794P 2017-04-14 2017-04-14
US62/485,794 2017-04-14

Publications (3)

Publication Number Publication Date
WO2018170393A2 WO2018170393A2 (en) 2018-09-20
WO2018170393A9 WO2018170393A9 (en) 2018-11-15
WO2018170393A3 true WO2018170393A3 (en) 2018-12-20

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PCT/US2018/022858 WO2018170393A2 (en) 2017-03-17 2018-03-16 Frame interpolation via adaptive convolution and adaptive separable convolution

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US (1) US11468318B2 (en)
KR (1) KR102474168B1 (en)
WO (1) WO2018170393A2 (en)

Families Citing this family (65)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US11778195B2 (en) * 2017-07-07 2023-10-03 Kakadu R & D Pty Ltd. Fast, high quality optical flow estimation from coded video
US11308361B1 (en) * 2017-07-07 2022-04-19 Twitter, Inc. Checkerboard artifact free sub-pixel convolution
US11557022B2 (en) * 2017-07-27 2023-01-17 Nvidia Corporation Neural network system with temporal feedback for denoising of rendered sequences
US11475542B2 (en) 2017-07-27 2022-10-18 Nvidia Corporation Neural network system with temporal feedback for adaptive sampling and denoising of rendered sequences
US10706890B2 (en) * 2017-08-24 2020-07-07 Intel Corporation Cinematic space-time view synthesis for enhanced viewing experiences in computing environments
US10776688B2 (en) 2017-11-06 2020-09-15 Nvidia Corporation Multi-frame video interpolation using optical flow
US11122238B1 (en) * 2017-11-07 2021-09-14 Twitter, Inc. Frame interpolation with multi-scale deep loss functions and generative adversarial networks
DE102018200534A1 (en) * 2018-01-15 2019-07-18 Robert Bosch Gmbh Method of operating an artificial neural network
US11019355B2 (en) * 2018-04-03 2021-05-25 Electronics And Telecommunications Research Institute Inter-prediction method and apparatus using reference frame generated based on deep learning
US10984245B1 (en) * 2018-06-11 2021-04-20 Facebook, Inc. Convolutional neural network based on groupwise convolution for efficient video analysis
KR102550327B1 (en) * 2018-09-21 2023-06-30 엘지디스플레이 주식회사 Method and apparatus for upscaling video
US11783707B2 (en) 2018-10-09 2023-10-10 Ford Global Technologies, Llc Vehicle path planning
JP7135697B2 (en) * 2018-10-11 2022-09-13 株式会社島津製作所 Analysis device, analysis system and analysis method
US11126915B2 (en) * 2018-10-15 2021-09-21 Sony Corporation Information processing apparatus and information processing method for volume data visualization
WO2020080873A1 (en) 2018-10-19 2020-04-23 Samsung Electronics Co., Ltd. Method and apparatus for streaming data
WO2020080665A1 (en) 2018-10-19 2020-04-23 Samsung Electronics Co., Ltd. Methods and apparatuses for performing artificial intelligence encoding and artificial intelligence decoding on image
WO2020080765A1 (en) 2018-10-19 2020-04-23 Samsung Electronics Co., Ltd. Apparatuses and methods for performing artificial intelligence encoding and artificial intelligence decoding on image
US11720997B2 (en) 2018-10-19 2023-08-08 Samsung Electronics Co.. Ltd. Artificial intelligence (AI) encoding device and operating method thereof and AI decoding device and operating method thereof
KR102312337B1 (en) * 2018-10-19 2021-10-14 삼성전자주식회사 AI encoding apparatus and operating method for the same, and AI decoding apparatus and operating method for the same
WO2020080709A1 (en) 2018-10-19 2020-04-23 Samsung Electronics Co., Ltd. Artificial intelligence encoding and artificial intelligence decoding methods and apparatuses using deep neural network
WO2020080698A1 (en) 2018-10-19 2020-04-23 삼성전자 주식회사 Method and device for evaluating subjective quality of video
KR102525578B1 (en) 2018-10-19 2023-04-26 삼성전자주식회사 Method and Apparatus for video encoding and Method and Apparatus for video decoding
KR102285738B1 (en) * 2018-10-19 2021-08-05 삼성전자주식회사 Method and apparatus for assessing subjective quality of a video
US20200137380A1 (en) * 2018-10-31 2020-04-30 Intel Corporation Multi-plane display image synthesis mechanism
CN112889084B (en) * 2018-11-08 2023-05-23 Oppo广东移动通信有限公司 Method, system and computer readable medium for improving color quality of image
CN111178491A (en) * 2018-11-09 2020-05-19 佳能株式会社 Method, device, system and storage medium for training and applying neural network model
CN109472315B (en) * 2018-11-15 2021-09-24 江苏木盟智能科技有限公司 Target detection method and system based on depth separable convolution
KR20200071404A (en) * 2018-12-11 2020-06-19 삼성전자주식회사 Image processing apparatus and operating method for the same
US11080835B2 (en) * 2019-01-09 2021-08-03 Disney Enterprises, Inc. Pixel error detection system
CN109919829A (en) * 2019-01-17 2019-06-21 北京达佳互联信息技术有限公司 Image Style Transfer method, apparatus and computer readable storage medium
GB2580671B (en) * 2019-01-22 2022-05-04 Toshiba Kk A computer vision system and method
US11461653B2 (en) * 2019-01-23 2022-10-04 StradVision, Inc. Learning method and learning device for CNN using 1xK or Kx1 convolution to be used for hardware optimization, and testing method and testing device using the same
US11288818B2 (en) * 2019-02-19 2022-03-29 The Trustees Of The University Of Pennsylvania Methods, systems, and computer readable media for estimation of optical flow, depth, and egomotion using neural network trained using event-based learning
CN109905624B (en) 2019-03-01 2020-10-16 北京大学深圳研究生院 Video frame interpolation method, device and equipment
KR20210090159A (en) 2019-03-25 2021-07-19 텔레다인 디지털 이미징, 아이엔씨. Methods and related devices for generating super-resolution images
EP3959882A1 (en) * 2019-04-23 2022-03-02 Telefonaktiebolaget LM Ericsson (publ) A computer software module, a device and a method for accelerating inference for compressed videos
CN110111366B (en) * 2019-05-06 2021-04-30 北京理工大学 End-to-end optical flow estimation method based on multistage loss
US10896356B2 (en) * 2019-05-10 2021-01-19 Samsung Electronics Co., Ltd. Efficient CNN-based solution for video frame interpolation
US11460851B2 (en) 2019-05-24 2022-10-04 Ford Global Technologies, Llc Eccentricity image fusion
US11521494B2 (en) 2019-06-11 2022-12-06 Ford Global Technologies, Llc Vehicle eccentricity mapping
US11662741B2 (en) 2019-06-28 2023-05-30 Ford Global Technologies, Llc Vehicle visual odometry
CN110427094B (en) * 2019-07-17 2021-08-17 Oppo广东移动通信有限公司 Display method, display device, electronic equipment and computer readable medium
CN110659379B (en) * 2019-09-24 2023-05-23 中南林业科技大学 Searchable encrypted image retrieval method based on deep convolution network characteristics
WO2021063119A1 (en) * 2019-10-01 2021-04-08 Guangdong Oppo Mobile Telecommunications Corp., Ltd. Method and apparatus for image processing, terminal
KR20210056179A (en) 2019-11-08 2021-05-18 삼성전자주식회사 AI encoding apparatus and operating method for the same, and AI decoding apparatus and operating method for the same
US10958869B1 (en) * 2019-11-14 2021-03-23 Huawei Technologies Co., Ltd. System, device and method for video frame interpolation using a structured neural network
KR102207736B1 (en) * 2020-01-14 2021-01-26 한국과학기술원 Frame interpolation, apparatus and method using deep neural network
CN111212287A (en) * 2020-01-15 2020-05-29 济南浪潮高新科技投资发展有限公司 Video compression method based on image interpolation method
US11074730B1 (en) 2020-01-23 2021-07-27 Netapp, Inc. Augmented reality diagnostic tool for data center nodes
KR102372046B1 (en) * 2020-03-12 2022-03-11 숭실대학교 산학협력단 Method of vessel structures extraction using artificial intelligence technique, recording medium and device for performing the method
US11508143B2 (en) 2020-04-03 2022-11-22 Disney Enterprises, Inc. Automated salience assessment of pixel anomalies
WO2021217653A1 (en) * 2020-04-30 2021-11-04 京东方科技集团股份有限公司 Video frame insertion method and apparatus, and computer-readable storage medium
CN113727141B (en) * 2020-05-20 2023-05-12 富士通株式会社 Interpolation device and method for video frames
CN111814479B (en) * 2020-07-09 2023-08-25 上海明略人工智能(集团)有限公司 Method and device for generating enterprise abbreviations and training model thereof
KR20220030084A (en) * 2020-09-02 2022-03-10 삼성전자주식회사 Method and apparatus of processing image
US11216656B1 (en) * 2020-12-16 2022-01-04 Retrocausal, Inc. System and method for management and evaluation of one or more human activities
KR20220092247A (en) * 2020-12-24 2022-07-01 삼성전자주식회사 Electronic apparatus and method for controlling thereof
CN113014936B (en) * 2021-02-24 2022-12-13 北京百度网讯科技有限公司 Video frame insertion method, device, equipment and storage medium
WO2022186620A1 (en) * 2021-03-04 2022-09-09 현대자동차주식회사 Video coding method and apparatus for improving prediction signals of intra prediction
US20220321830A1 (en) * 2021-04-06 2022-10-06 Adobe Inc. Optimization of adaptive convolutions for video frame interpolation
CN113132664B (en) * 2021-04-19 2022-10-04 科大讯飞股份有限公司 Frame interpolation generation model construction method and video frame interpolation method
GB2609708B (en) * 2021-05-25 2023-10-25 Samsung Electronics Co Ltd Method and apparatus for video recognition
US20220400226A1 (en) * 2021-06-14 2022-12-15 Microsoft Technology Licensing, Llc Video Frame Interpolation Via Feature Pyramid Flows
CN113379869B (en) * 2021-07-23 2023-03-24 浙江大华技术股份有限公司 License plate image generation method and device, electronic equipment and storage medium
CN113762349A (en) * 2021-08-11 2021-12-07 同济大学 Lightweight aliasing dense network classification method and system for marine organisms

Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2016132146A1 (en) * 2015-02-19 2016-08-25 Magic Pony Technology Limited Visual processing using sub-pixel convolutions

Family Cites Families (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5353119A (en) * 1990-11-15 1994-10-04 Sony United Kingdom Limited Format conversion of digital video signals, integration of digital video signals into photographic film material and the like, associated signal processing, and motion compensated interpolation of images
US20030189579A1 (en) * 2002-04-05 2003-10-09 Pope David R. Adaptive enlarging and/or sharpening of a digital image
US9039621B2 (en) * 2011-07-27 2015-05-26 The United States of America National Institutes of Health (NIH), U.S. Dept. of Health and Human Services (DHHS), NIH Division of Extramural Inventions and Technology Resources (DEITR) Non-invasive ultrasonic gingival tissue diagnosis
US9418458B2 (en) 2015-01-05 2016-08-16 Superfish Ltd. Graph image representation from convolutional neural networks
CA2994713C (en) * 2015-08-15 2019-02-12 Salesforce.Com, Inc. Three-dimensional (3d) convolution with 3d batch normalization
JP6700712B2 (en) * 2015-10-21 2020-05-27 キヤノン株式会社 Convolution operation device
WO2017125980A1 (en) * 2016-01-21 2017-07-27 ソニー株式会社 Information processing device, information processing method, and program
US10860879B2 (en) * 2016-05-16 2020-12-08 Raytheon Technologies Corporation Deep convolutional neural networks for crack detection from image data

Patent Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2016132146A1 (en) * 2015-02-19 2016-08-25 Magic Pony Technology Limited Visual processing using sub-pixel convolutions

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
GUCAN LONG ET AL.: "Learning Image Matching by Simply Watching Video", ECCV 2016, 2016, pages 434 - 450, XP047355274 *
HAITAM BEN YAHIA: "Frame Interpolation using Convolutional Neural Networks on 2D animation", BACHELOR THESIS, 24 June 2016 (2016-06-24), XP055558906 *

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Publication number Publication date
KR102474168B1 (en) 2022-12-06
US11468318B2 (en) 2022-10-11
WO2018170393A2 (en) 2018-09-20
WO2018170393A9 (en) 2018-11-15
KR20190132415A (en) 2019-11-27
US20200012940A1 (en) 2020-01-09

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