FlowNet 2.0: Evolution of Optical Flow Estimation with Deep Networks
-
Updated
Oct 9, 2018 - Python
#
flownet2
Here are 8 public repositories matching this topic...
Consist of four different approaches for generating optical flow and can be demonstrated in Colab.
-
Updated
Dec 14, 2020 - Python
Dockerized fast-artistic-videos
-
Updated
Jun 2, 2020 - Python
In this repository, we deal with the task of video frame interpolation with estimated optical flow. To estimate the optical flow we use pre-trained FlowNet2 deep learning model and experiment by fine-tuning it. We explore the interpolation performance on Spheres dataset and Corridor dataset.
-
Updated
Apr 5, 2021 - Python
Video Super Resolution with depth map and optical flow for unnatural object flow
optical-flow
super-resolution
depth-map
object-segmentation
video-super-resolution
flownet2
video-object-segmentation
mvdepthnet
rgmp
-
Updated
Aug 13, 2020 - Python
Pytorch implementation of our method for high-resolution (e.g. 2048x1024) photorealistic video-to-video translation.
algorithm
deep-learning
optical-flow
cityscapes
flownet2
densepose
pytorch-implementation
vid2vid
video-to-video-translation
-
Updated
Sep 20, 2018 - Python
Improve performance of PWC-Net in foggy scenes
-
Updated
Nov 14, 2019 - Python
Improve this page
Add a description, image, and links to the flownet2 topic page so that developers can more easily learn about it.
Add this topic to your repo
To associate your repository with the flownet2 topic, visit your repo's landing page and select "manage topics."