computer-vision-2

Image Morphing

3260 papers • 126 benchmarks • 313 datasets

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Benchmarks

These leaderboards are used to track progress in image-morphing-2

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Libraries

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Use these libraries to find image-morphing-2 models and implementations

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Most implemented papers

Image2StyleGAN: How to Embed Images Into the StyleGAN Latent Space?

Peter Wonka, Yipeng Qin, Rameen Abdal•Thu Apr 04 2019

This work proposes an efficient algorithm to embed a given image into the latent space of StyleGAN, which enables semantic image editing operations that can be applied to existing photographs.

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Kornia: an Open Source Differentiable Computer Vision Library for PyTorch

Dmytro Mishkin, Edgar Riba, D. Ponsa, Ethan Rublee, Gary R. Bradski•Fri Oct 04 2019

Kornia is composed of a set of modules containing operators that can be inserted inside neural networks to train models to perform image transformations, camera calibration, epipolar geometry, and low level image processing techniques, such as filtering and edge detection that operate directly on high dimensional tensor representations.

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StyleGAN2 Distillation for Feed-forward Image Manipulation

Yuri Viazovetskyi, V. Ivashkin, Evgenii Kashin•Fri Mar 06 2020

It is shown that the quality of generation using the proposed pipeline is comparable to StyleGAN2 backpropagation and current state-of-the-art methods in these particular tasks, and the resulting pipeline is an alternative to existing GANs, trained on unpaired data.

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Exploiting Deep Generative Prior for Versatile Image Restoration and Manipulation

Chen Change Loy, Dahua Lin, P. Luo, Xingang Pan, Xiaohang Zhan, Bo Dai•Sun Mar 29 2020

This work presents an effective way to exploit the image prior captured by a generative adversarial network (GAN) trained on large-scale natural images and allows the generator to be fine-tuned on-the-fly in a progressive manner regularized by feature distance obtained by the discriminator in GAN.

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Image Morphing With Perceptual Constraints and STN Alignment

Richard Zhang, Eli Shechtman, Connelly Barnes, D. Cohen-Or, N. Fish, Lilach Perry•Tue Apr 28 2020

A conditional generative adversarial network (GAN) morphing framework operating on a pair of input images is proposed, trained to synthesize frames corresponding to temporal samples along the transformation, and learns a proper shape prior that enhances the plausibility of intermediate frames.

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Vulnerability Analysis of Face Morphing Attacks from Landmarks and Generative Adversarial Networks

S. Marcel, Eklavya Sarkar, Pavel Korshunov, Laurent Colbois•Tue Dec 08 2020

The experiments demonstrate that VGG-Face, while being less accurate face recognition system compared to FaceNet, is also less vulnerable to morphing attacks, and that naive morphs generated with a StyleGAN do not pose a significant threat.

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Paper Graph

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