NDLI: Flow-based frame interpolation networks combined with occlusion-aware mask estimation

Content Provider	IET Digital Library
Author	Zhang, Dacheng Lei, Weimin Zhang, Wei Chen, Xinyi
Abstract	Frame interpolation is one of the most challenging tasks in the video processing field. Recent advances have demonstrated that the deep learning-based frame interpolation methods are promising. However, the experiments show that most existing deep learning-based methods have the same problem as traditional methods. When these algorithms handle severe occlusions, they will produce distortions, especially around the motion boundaries. To better synthesise the image of the motion areas, the authors design a mask-guided frame synthesis model, which consists of multiple components, based on deep convolutional neural networks. The proposed model first estimates the asymmetric bi-directional optical flows from the intermediate frame to the input frames. Then it estimates the occlusion-aware masks, which can compensate for the optical flow inaccuracy based on optical flows and correlation information. Finally, the warped frames are adaptively fused under the guidance of the masks to generate a high-quality intermediate frame. Furthermore, to generate more realistic video frames, they train the network model with the pixel-based loss and the feature-based loss in a step-by-step way. In the experiment, they analyse the proposed model and compare it with the high-performance methods, both qualitative and quantitative results show that their method performs better.
Starting Page	4579
Ending Page	4587
Page Count	9
ISSN	17519659
Volume Number	14
e-ISSN	17519667
Issue Number	Issue 17, Dec (2020)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-ipr.2020.0586
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-ipr/14/17
Journal	IET Image Processing
Publisher Date	2021-01-18
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Computer Vision And Image Processing Technique Deep Convolutional Neural Network Deep Learning-based Frame Interpolation Method Existing Deep Learning-based Method Feature Extraction Feature-based Loss Frame Interpolation Network High-performance Method High-quality Intermediate Frame Image Motion Analysis Image Sequence Input Frames Interpolation Interpolation And Function Approximation Learning in AI Mask-guided Frame Synthesis Model Motion Areas Motion Boundaries Motion Estimation Network Model Neural Nets Numerical Analysis Occlusion-aware Mask Estimation Occlusion-aware Masks Optical Flow Inaccuracy Optical Flows Optical, Image And Video Signal Processing Pixel-based Loss Realistic Video Frames Severe Occlusions Video Processing Field Video Signal Processing Warped Frames
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering Computer Vision and Pattern Recognition Software

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