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Conditional Image Generation

25 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.

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Greatest papers with code

Improved Techniques for Training GANs

NeurIPS 2016 tensorflow/models

We present a variety of new architectural features and training procedures that we apply to the generative adversarial networks (GANs) framework.

CONDITIONAL IMAGE GENERATION SEMI-SUPERVISED IMAGE CLASSIFICATION

Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks

19 Nov 2015tensorflow/models

In recent years, supervised learning with convolutional networks (CNNs) has seen huge adoption in computer vision applications.

CONDITIONAL IMAGE GENERATION UNSUPERVISED REPRESENTATION LEARNING

Self-Attention Generative Adversarial Networks

arXiv 2018 jantic/DeOldify

In this paper, we propose the Self-Attention Generative Adversarial Network (SAGAN) which allows attention-driven, long-range dependency modeling for image generation tasks.

CONDITIONAL IMAGE GENERATION

High-Resolution Image Synthesis and Semantic Manipulation with Conditional GANs

CVPR 2018 NVIDIA/pix2pixHD

We present a new method for synthesizing high-resolution photo-realistic images from semantic label maps using conditional generative adversarial networks (conditional GANs).

CONDITIONAL IMAGE GENERATION IMAGE-TO-IMAGE TRANSLATION INSTANCE SEGMENTATION SEMANTIC SEGMENTATION

Improved Training of Wasserstein GANs

NeurIPS 2017 igul222/improved_wgan_training

Generative Adversarial Networks (GANs) are powerful generative models, but suffer from training instability.

CONDITIONAL IMAGE GENERATION

Conditional Image Generation with PixelCNN Decoders

NeurIPS 2016 openai/pixel-cnn

This work explores conditional image generation with a new image density model based on the PixelCNN architecture.

#4 best model for Image Generation on CIFAR-10 (NLL Test metric)

CONDITIONAL IMAGE GENERATION

Conditional Image Synthesis With Auxiliary Classifier GANs

ICML 2017 kaonashi-tyc/zi2zi

We expand on previous work for image quality assessment to provide two new analyses for assessing the discriminability and diversity of samples from class-conditional image synthesis models.

CONDITIONAL IMAGE GENERATION IMAGE QUALITY ASSESSMENT

High-Fidelity Image Generation With Fewer Labels

6 Mar 2019google/compare_gan

Deep generative models are becoming a cornerstone of modern machine learning.

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

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