sampepose/flownet2-tf
A TensorFlow implementation of FlowNet 2.0 deep neural networks for optical flow estimation between image pairs.
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This repository provides a TensorFlow implementation of FlowNet 2.0, a deep learning architecture for optical flow estimation in computer vision. It includes multiple model variants (FlowNetC, S, CS, CSS, SD, and the stacked FlowNet2) and supports both inference and training. The models use convolutional neural networks to estimate motion vectors between consecutive image frames. The repository includes pre-trained checkpoints, benchmark timing data, and scripts for generating flow predictions from image pairs.
Frequently asked
- What is sampepose/flownet2-tf?
- A TensorFlow implementation of FlowNet 2.0 deep neural networks for optical flow estimation between image pairs.
- Is flownet2-tf open source?
- Yes — sampepose/flownet2-tf is open source, released under the MIT license.
- What language is flownet2-tf written in?
- sampepose/flownet2-tf is primarily written in Python.
- How popular is flownet2-tf?
- sampepose/flownet2-tf has 408 stars on GitHub.
- Where can I find flownet2-tf?
- sampepose/flownet2-tf is on GitHub at https://github.com/sampepose/flownet2-tf.