Pose Transfer

28 papers with code • 2 benchmarks • 2 datasets

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Most implemented papers

Pose Guided Person Image Generation

chuanqichen/deepcoaching NeurIPS 2017

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.

Progressive Pose Attention Transfer for Person Image Generation

tengteng95/Pose-Transfer CVPR 2019

This paper proposes a new generative adversarial network for pose transfer, i. e., transferring the pose of a given person to a target pose.

Controllable Person Image Synthesis with Attribute-Decomposed GAN

menyifang/adgan CVPR 2020

This paper introduces the Attribute-Decomposed GAN, a novel generative model for controllable person image synthesis, which can produce realistic person images with desired human attributes (e. g., pose, head, upper clothes and pants) provided in various source inputs.

XingGAN for Person Image Generation

Ha0Tang/XingGAN ECCV 2020

We propose a novel Generative Adversarial Network (XingGAN or CrossingGAN) for person image generation tasks, i. e., translating the pose of a given person to a desired one.

Disentangled Person Image Generation

charliememory/Disentangled-Person-Image-Generation CVPR 2018

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.

Deformable GANs for Pose-based Human Image Generation

AliaksandrSiarohin/pose-gan CVPR 2018

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

Dense Intrinsic Appearance Flow for Human Pose Transfer

ly015/intrinsic_flow CVPR 2019

Unlike existing methods, we propose to estimate dense and intrinsic 3D appearance flow to better guide the transfer of pixels between poses.

Guided Image-to-Image Translation with Bi-Directional Feature Transformation

vt-vl-lab/Guided-pix2pix ICCV 2019

We address the problem of guided image-to-image translation where we translate an input image into another while respecting the constraints provided by an external, user-provided guidance image.

Neural Pose Transfer by Spatially Adaptive Instance Normalization

jiashunwang/Neural-Pose-Transfer CVPR 2020

Pose transfer has been studied for decades, in which the pose of a source mesh is applied to a target mesh.

Region-adaptive Texture Enhancement for Detailed Person Image Synthesis

Lotayou/RATE 26 May 2020

The ability to produce convincing textural details is essential for the fidelity of synthesized person images.