Abstract提出了一种紧凑而有效的光流 CNN 模型,称为 PWC-Net。PWC-Net 的设计遵循简单而成熟的原则:金字塔结构、warping 和 cost volume 的使用。 PWC-Net 采用可学习的特征金字塔结构,利用当前的光流估计值对…
We present a consistent numerical scheme based on two nested fixed point iterations. By proving that this scheme implements a coarse-to-fine warping strategy, we give a theoretical foundation for warping which has been used on a mainly experimental basis so far. Our evaluation demonstrates that ...
opencvmachine-learningdeep-learninggamingfpsanticheatoptical-flowanti-cheatopencv-pythonfps-shooter UpdatedNov 20, 2021 Python philferriere/tfoptflow Star526 Optical Flow Prediction with TensorFlow. Implements "PWC-Net: CNNs for Optical Flow Using Pyramid, Warping, and Cost Volume," by Deqing Sun et...
PWC-Net是根据简单而完善的原则设计的:pyramidal processing, warping, and the use of a cost volume。在可学习的特征金字塔中,PWC-Net使用当前光流估计来warping第二幅图像的CNN特征。然后,它使用warping的特征和第一图像的特征来构建代价空间,该代价空间由CNN处理以估计光流。
PWC-Net是一种设计简洁而全面的神经网络架构，旨在解决光学流动问题。它通过金字塔处理、warp操作和成本体积构建，实现对图像序列中像素间运动的高效估计。该网络的核心创新在于其可学习特征金字塔，利用当前的光流估计对第二幅图像的CNN特征进行warp操作，以此来捕捉图像间运动的细微差异。通过这种方式，PWC-...
This model can learn optical flow forward and backward automatically and a new loss function was proposed. They used PWC-Net [42] which is based on three principles: warping, pyramidal processing and the use of cost volume is shown in Fig. 16 is a compact and operative CNN model for the...
The classification is done with a proposed novel time-series classification method including a metric for comparing optical flow histograms. The study in Ref. [21] proposes an optical flow-based representation which groups the optical flow vectors of whole video segment according to angular values. ...
1、摘要:PWC-Net是根据简单和完善的原则设计的:金字塔处理、warp和 cost volume.(个人理解为相关性)。PWC-Net采用一个可学习的特征金字塔,使用当前的光流估计来warp第二幅图像的CNN特征。2.本文方法: 1)整…
LiteFlowNet: A Lightweight Convolutional Neural Network for Optical Flow Estimation,程序员大本营,技术文章内容聚合第一站。
To overcome this limitation, we propose an automatic video colorization based on contrastive learning and optical flow. Contrastive learning optimizes the temporal correlation loss between the feature vectors of the gray video frame patches and the generated color video frame patches during training, ...