# Gesture-to-Gesture Translation

6 papers with code • 2 benchmarks • 0 datasets

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# Pose Guided Person Image Generation

This paper proposes the novel Pose Guided Person Generation Network (PG$^2$) that allows to synthesize person images in arbitrary poses, based on an image of that person and a novel pose.

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# Disentangled Person Image Generation

Generating novel, yet realistic, images of persons is a challenging task due to the complex interplay between the different image factors, such as the foreground, background and pose information.

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# Deformable GANs for Pose-based Human Image Generation

Specifically, given an image of a person and a target pose, we synthesize a new image of that person in the novel pose.

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# GestureGAN for Hand Gesture-to-Gesture Translation in the Wild

14 Aug 2018

Therefore, this task requires a high-level understanding of the mapping between the input source gesture and the output target gesture.

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# Gesture-to-Gesture Translation in the Wild via Category-Independent Conditional Maps

12 Jul 2019

In this work, we propose a novel GAN architecture that decouples the required annotations into a category label - that specifies the gesture type - and a simple-to-draw category-independent conditional map - that expresses the location, rotation and size of the hand gesture.

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# Unified Generative Adversarial Networks for Controllable Image-to-Image Translation

12 Dec 2019

The proposed model consists of a single generator and a discriminator taking a conditional image and the target controllable structure as input.

1