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computer-vision-5

Video Stabilization

3260 papers • 126 benchmarks • 313 datasets

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Most implemented papers

Hybrid Neural Fusion for Full-frame Video Stabilization

Ming-Hsuan Yang, Wei-Sheng Lai, Yung-Yu Chuang, Yu-Lun Liu, Jia-Bin Huang•Wed Feb 10 2021

This work presents a frame synthesis algorithm to achieve full-frame video stabilization that first estimate dense warp fields from neighboring frames and then synthesize the stabilized frame by fusing the warped contents.

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DUT: Learning Video Stabilization by Simply Watching Unstable Videos

D. Tao, Yufei Xu, Jing Zhang, S. Maybank•Sun Nov 29 2020

This paper attempts to tackle the video stabilization problem in a deep unsupervised learning manner, which borrows the divide-and-conquer idea from traditional stabilizers while leveraging the representation power of DNNs to handle the challenges in real-world scenarios.

66 0

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Robust Gyroscope-Aided Camera Self-Calibration

Juho Kannala, Santiago Cortés Reina, A. Solin•Wed May 30 2018

A model for estimating the parameters on the fly by fusing gyroscope and camera data, both readily available in modern day smartphones, is proposed and shown to outperform existing methods in robustness and insensitivity to initialization.

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Real-Time Selfie Video Stabilization

R. Ramamoorthi, Ji-yang Yu, Ke-Li Cheng, M. Sarkis, N. Bi•Thu Sep 03 2020

A 1D linear convolutional network is used to directly infer the rigid moving least squares warping which implicitly balances between the global rigidity and local flexibility and produces visually and quantitatively better results than previous real-time general video stabilization methods.

26 0

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Deep Iterative Frame Interpolation for Full-frame Video Stabilization

Jinsoo Choi, I. Kweon•Wed Sep 04 2019

This work proposes an unsupervised deep approach to full-frame video stabilization that can generate video frames without cropping and low distortion, and utilizes frame interpolation techniques to generate in between frames, leading to reduced inter-frame jitter.

82 0

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Deep Motion Blind Video Stabilization

Tae Hyun Kim, M. K. Ali, Sangjoon Yu•Wed Nov 18 2020

This work aims to declutter this over-complicated formulation of video stabilization with the help of a novel dataset that contains pairs of training videos with similar perspective but different motion, and verify its effectiveness by successfully learning motion blind full-frame video stabilization through employing strictly conventional generative techniques.

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A Method for Detection of Small Moving Objects in UAV Videos

Vladan Stojnić, V. Risojević, M. Mustra, Vedran Jovanovic, J. Filipi, N. Kezic, Z. Babic•Wed Feb 10 2021

The experimental results on detection of flying honeybees show that by using a combination of classical computer vision techniques and CNNs, as well as synthetic training sets, the proposed approach overcomes the problems associated with direct application of CNNs to the given problem and achieves an average F1-score of 0.86 on real-world videos.

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Deep Online Fused Video Stabilization

Wei-Sheng Lai, Zhenmei Shi, Fuhao Shi, Chia-Kai Liang, Yingyu Liang•Mon Feb 01 2021

To the best of the knowledge, this is the first DNN solution that adopts both sensor data and image content for video stabilization, and it outperforms the state-of-art alternative solutions via quantitative evaluations and a user study.

35 0

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Video Stabilization | State-of-the-Art