Video Frame Interpolation with Transformer
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022 Video frame interpolation (VFI), which aims to synthesize intermediate frames of a video, has made remarkable progress with development of deep convolutional networks over past years. Existing methods built upon convolutional networks generally face challenges of handling large motion due to the locality of convolution operations.
Lu, Liying +4 more
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Conformal and empirical transformation between the PL-ETRF89 and PL-ETRF2000 reference frames using the new adjustment of the former Polish I class triangulation network [PDF]
Geodesy and Cartography, 2021 The European reference frame ETRF2000 was introduced on the territory of Poland on 1 July 2013, named PL-ETRF2000, as a result of the appropriate measurement campaign 2008-2011.
Roman Kadaj
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Residual Learning of Video Frame Interpolation Using Convolutional LSTM
IEEE Access, 2020 Video frame interpolation aims to generate intermediate frames between the original frames. This produces videos with a higher frame rate and creates smoother motion.
Keito Suzuki, Masaaki Ikehara
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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
core +1 more source
FILM: Frame Interpolation for Large Motion
, 2022 We present a frame interpolation algorithm that synthesizes multiple intermediate frames from two input images with large in-between motion. Recent methods use multiple networks to estimate optical flow or depth and a separate network dedicated to frame synthesis. This is often complex and requires scarce optical flow or depth ground-truth.
Reda, Fitsum +5 more
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Subjective Annotation for a Frame Interpolation Benchmark using Artefact Amplification [PDF]
, 2020 Current benchmarks for optical flow algorithms evaluate the estimation either directly by comparing the predicted flow fields with the ground truth or indirectly by using the predicted flow fields for frame interpolation and then comparing the ...
Bruhn, Andrés +4 more
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Video frame interpolation via residual blocks and feature pyramid networks
IET Image Processing, 2023 Various deep learning‐based video frame interpolation methods have been proposed in the past few years, but how to generate high quality interpolated frames in videos with large motions, complex backgrounds and rich textures is still a challenging issue.
Xiaohui Yang +4 more
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A concealment based approach to distributed video coding [PDF]
, 2008 This paper presents a concealment based approach to distributed video coding that uses hybrid key/WZ frames via an FMO type interleaving of macroblocks. Our motivation stems from a previous work of ours that showed promising results relative to the more ...
Agrafiotis, D +2 more
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Multiple Video Frame Interpolation Method Based on Transformer and Enhanced Deformable Separable Convolution [PDF]
Jisuanji gongchengExisting multiple Video Frame Interpolation (VFI) methods rely on optical flow or Convolutional Neural Networks (CNN) for implementation; however, they struggle to handle scenes with large motions effectively because of the inherent limitations of ...
SHI Changtong, SHAN Hongtao
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Motion‐based frame interpolation for film and television effects
IET Computer Vision, 2020 Frame interpolation is the process of synthesising a new frame in‐between existing frames in an image sequence. It has emerged as a key algorithmic module in motion picture effects.
Anil Kokaram +5 more
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