Generate optical flow with conditional generative adversarial network

Lingqi Wu; Zongqing Lu; Ting Tang; Qingmin Liao

doi:10.1117/12.2503297

9 August 2018 Generate optical flow with conditional generative adversarial network

Lingqi Wu, Zongqing Lu, Ting Tang, Qingmin Liao

Proceedings Volume 10806, Tenth International Conference on Digital Image Processing (ICDIP 2018); 108064J (2018) https://doi.org/10.1117/12.2503297
Event: Tenth International Conference on Digital Image Processing (ICDIP 2018), 2018, Shanghai, China

Abstract

As the cGANs achieves great success on pix to pix problem [12], we proposed a new architecture based on cGAN to solve our optical flow estimation problem. Specifically, we propose a loss function which consists of an adversarial loss and a content loss. The adversarial loss is the pixel-to-pixel loss. We use a discriminator network which is trained to differentiate the ground-truth flow and the generated flow on pixel space. The content loss focuses on perceptual similarity of the ground-truth flow and the generated flow. Our architecture (FlowGan) contains a generator based on FlowNetS with Dense Block to make it deeper and a Markovian discriminator to classify image patch instead of the whole image. We train our network with FlyingChairs datasets and evaluated our network on MPISintel. FlowGan can get competitive results with practical speed.

Citation Download Citation

Lingqi Wu, Zongqing Lu, Ting Tang, and Qingmin Liao "Generate optical flow with conditional generative adversarial network", Proc. SPIE 10806, Tenth International Conference on Digital Image Processing (ICDIP 2018), 108064J (9 August 2018); https://doi.org/10.1117/12.2503297

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
8 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Optical flow

Convolution

Gallium nitride

Network architectures

Optical networks

Image segmentation

Associative arrays

Show All Keywords

Keywords/Phrases

Search In:

Publication Years