A Spatial Prediction-Based Motion-Compensated Frame Rate Up-Conversion
Future Internet, 2019 In Multimedia Internet of Things (IoT), in order to reduce the bandwidth consumption of wireless channels, Motion-Compensated Frame Rate Up-Conversion (MC-FRUC) is often used to support the low-bitrate video communication.
Yanli Li, Wendan Ma, Yue Han
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A Stacked Deep MEMC Network for Frame Rate Up Conversion and its Application to HEVC
IEEE Access, 2020 Optical flows and video frame interpolation are considered as a chicken-egg problem such that one problem affects the other and vice versa. This paper presents a stack of deep networks to estimate intermediate optical flows from the very first ...
Nguyen Van Thang +2 more
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Multi-Scheme Frame Rate Up-Conversion Using Space-Time Saliency
IEEE Access, 2018 We propose a novel frame rate up-conversion algorithm, which adaptively selects multiple motion estimation (ME) schemes to generate absent frames according to the space-time saliency.
Ran Li, Yongfeng Lv, Zhenghui Liu
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Hierarchical Motion Estimation for Small Objects in Frame-Rate Up-Conversion
IEEE Access, 2018 Block-based hierarchical motion estimations are widely used for frame interpolation in frame-rate up-conversion and are successful in generating high-quality interpolations.
Nguyen Van Thang +4 more
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Frame Rate Up-Conversion Using Key Point Agnostic Frequency-Selective Mesh-to-Grid Resampling [PDF]
IEEE International Conference on Acoustics, Speech, and Signal Processing, 2021 High frame rates are desired in many fields of application. As in many cases the frame repetition rate of an already captured video has to be increased, frame rate up-conversion (FRUC) is of high interest. We conduct a motion compensated approach.
Viktoria Heimann +2 more
semanticscholar +1 more source
Triple Motion Estimation and Frame Interpolation based on Adaptive Threshold for Frame Rate Up-Conversion [PDF]
arXiv.org, 2022 In this paper, we propose a novel motion-compensated frame rate up-conversion (MC-FRUC) algorithm. The proposed algorithm creates interpolated frames by first estimating motion vectors using unilateral (jointing forward and backward) and bilateral motion
Hanieh Naderi, M. Rahmati
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Video Frame Rate Up-Conversion via Spatio-Temporal Generative Adversarial Networks
Journal of Image and Graphics, 2021 Video quality has become more important due to the development of information and communication technology. In this study, we propose a spatio-temporal super-resolution method using a Generative Adversarial Network (GAN) in order to achieve a higher ...
Naomichi Takada, T. Omori
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Deep Video Frame Rate Up-conversion Network using Feature-based Progressive Residue Refinement
VISIGRAPP, 2022 : In this paper, we propose a deep learning-based network for video frame rate up-conversion (or video frame interpolation). The proposed optical flow-based pipeline employs deep features extracted to learn residue maps for progressively refining the ...
Jinglei Shi, Xiaoran Jiang, C. Guillemot
semanticscholar +1 more source
Homography-guided stereo matching for wide-baseline image interpolation
Computational Visual Media, 2021 Image interpolation has a wide range of applications such as frame rate-up conversion and free viewpoint TV. Despite significant progresses, it remains an open challenge especially for image pairs with large displacements. In this paper, we first propose
Yuan Chang +3 more
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A reconfigurable frame interpolation hardware architecture for high definition video [PDF]
, 2009 Since Frame Rate Up-Conversion (FRC) is started to be used in recent consumer electronics products like High Definition TV, real-time and low cost implementation of FRC algorithms has become very important.
Hamzaoglu, Ilker +3 more
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