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Conditional Image Generation

51 papers with code · Computer Vision
Subtask of Image Generation

Conditional image generation is the task of generating new images from a dataset conditional on their class.

( Image credit: PixelCNN++ )

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Greatest papers with code

GANimation: Anatomically-aware Facial Animation from a Single Image

ECCV 2018 albertpumarola/GANimation

Recent advances in Generative Adversarial Networks (GANs) have shown impressive results for task of facial expression synthesis.

CONDITIONAL IMAGE GENERATION FACE GENERATION IMAGE-TO-IMAGE TRANSLATION

TorchGAN: A Flexible Framework for GAN Training and Evaluation

8 Sep 2019torchgan/torchgan

The key features of TorchGAN are its extensibility, built-in support for a large number of popular models, losses and evaluation metrics, and zero overhead compared to vanilla PyTorch.

CONDITIONAL IMAGE GENERATION

cGANs with Projection Discriminator

ICLR 2018 pfnet-research/sngan_projection

We propose a novel, projection based way to incorporate the conditional information into the discriminator of GANs that respects the role of the conditional information in the underlining probabilistic model.

CONDITIONAL IMAGE GENERATION SUPER RESOLUTION SUPER-RESOLUTION

Invertible Conditional GANs for image editing

19 Nov 2016LynnHo/AttGAN-Tensorflow

Generative Adversarial Networks (GANs) have recently demonstrated to successfully approximate complex data distributions.

CONDITIONAL IMAGE GENERATION IMAGE-TO-IMAGE TRANSLATION

MixNMatch: Multifactor Disentanglement and Encoding for Conditional Image Generation

CVPR 2020 Yuheng-Li/MixNMatch

We present MixNMatch, a conditional generative model that learns to disentangle and encode background, object pose, shape, and texture from real images with minimal supervision, for mix-and-match image generation.

CONDITIONAL IMAGE GENERATION

GP-GAN: Towards Realistic High-Resolution Image Blending

21 Mar 2017wuhuikai/GP-GAN

To the best of our knowledge, it's the first work that explores the capability of GANs in high-resolution image blending task.

CONDITIONAL IMAGE GENERATION

Stacked Generative Adversarial Networks

CVPR 2017 xunhuang1995/SGAN

In this paper, we propose a novel generative model named Stacked Generative Adversarial Networks (SGAN), which is trained to invert the hierarchical representations of a bottom-up discriminative network.

CONDITIONAL IMAGE GENERATION

FineGAN: Unsupervised Hierarchical Disentanglement for Fine-Grained Object Generation and Discovery

CVPR 2019 kkanshul/finegan

We propose FineGAN, a novel unsupervised GAN framework, which disentangles the background, object shape, and object appearance to hierarchically generate images of fine-grained object categories.

CONDITIONAL IMAGE GENERATION FINE-GRAINED VISUAL CATEGORIZATION IMAGE CLUSTERING

Improved ArtGAN for Conditional Synthesis of Natural Image and Artwork

31 Aug 2017cs-chan/ArtGAN

Qualitatively, we demonstrate that ArtGAN is able to generate plausible-looking images on Oxford-102 and CUB-200, as well as able to draw realistic artworks based on style, artist, and genre.

CONDITIONAL IMAGE GENERATION

ArtGAN: Artwork Synthesis with Conditional Categorical GANs

11 Feb 2017cs-chan/ArtGAN

This paper proposes an extension to the Generative Adversarial Networks (GANs), namely as ARTGAN to synthetically generate more challenging and complex images such as artwork that have abstract characteristics.

ART ANALYSIS CONDITIONAL IMAGE GENERATION