WebLiteFlowNet is a lightweight, fast, and accurate opitcal flow CNN. We develop several specialized modules including pyramidal features, cascaded flow inference (cost volume + sub-pixel refinement), feature warping (f-warp) layer, and flow regularization by feature-driven local convolution (f-lconv) layer. Webpytorch-liteflownet3. This is a personal reimplementation of LiteFlowNet3 [1] using PyTorch, which is inspired by the pytorch-liteflownet implementation of LiteFlowNet by sniklaus. Should you be making use of this work, please cite the paper accordingly. Also, make sure to adhere to the licensing terms of the authors.
【光流】——liteflownet2论文与代码浅析_wx6135db1f08cc4的技 …
Web18 mei 2024 · LiteFlowNet: A Lightweight Convolutional Neural Network for Optical Flow Estimation. FlowNet2, the state-of-the-art convolutional neural network (CNN) for optical flow estimation, requires over 160M parameters to achieve accurate flow estimation. In this paper we present an alternative network that outperforms FlowNet2 on the challenging Sintel ... stanley ct13c
【光流】——liteflownet2论文与代码浅析_农夫山泉2号的博客 …
WebThe author of the original LiteFlowNet TF implementation believes it is due to a slightly different feature warping implementation than in the original work. License. Original materials are provided for research purposes only, and commercial use requires consent of the original author. Web14 jan. 2024 · LiteFlowNet:用于光流估计的轻量级卷积神经网络 摘要 1.介绍 2. 相关工作 变分方法。 机器学习方法。 基于 CNN 的方法。 3. LiteFlowNet 金字塔特征提取。 特征扭曲。 3.1. 级联流推断 第一流推理(描述符匹配) 3.2. 流正则化 4. 实验 网络细节。 训练详情。 4.1. 结果 4.2. 运行时间和参数 4.3. 消融研究 特征扭曲。 描述符匹配。 5. 结论 6. 附录 摘 … Web2 jun. 2024 · LiteFlowNet Figure4: LiteFlowNet architecture The name itself suggests it is the lighter version of FlowNet 2.0 but with more accurate results. The architecture consists of NetC (pyramidal... perth cfdc