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Conditional Image Generation

50 papers with code ยท 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++ )

Benchmarks

Latest papers without code

Controllable Image Synthesis via SegVAE

16 Jul 2020

We also apply an off-the-shelf image-to-image translation model to generate realistic RGB images to better understand the quality of the synthesized semantic maps.

CONDITIONAL IMAGE GENERATION IMAGE-TO-IMAGE TRANSLATION

Lessons Learned from the Training of GANs on Artificial Datasets

13 Jul 2020

Therefore, in order to conduct a thorough study on GANs while obviating unnecessary interferences introduced by the datasets, we train them on artificial datasets where there are infinitely many samples and the real data distributions are simple, high-dimensional and have structured manifolds.

CONDITIONAL IMAGE GENERATION

Attentive Normalization for Conditional Image Generation

CVPR 2020

Traditional convolution-based generative adversarial networks synthesize images based on hierarchical local operations, where long-range dependency relation is implicitly modeled with a Markov chain.

CONDITIONAL IMAGE GENERATION SEMANTIC SIMILARITY SEMANTIC TEXTUAL SIMILARITY

MixNMatch: Multifactor Disentanglement and Encoding for Conditional Image Generation

CVPR 2020

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

Evaluation Metrics for Conditional Image Generation

26 Apr 2020

We present two new metrics for evaluating generative models in the class-conditional image generation setting.

CONDITIONAL IMAGE GENERATION

Lesion Conditional Image Generation for Improved Segmentation of Intracranial Hemorrhage from CT Images

30 Mar 2020

A lesion conditional image (segmented mask) is an input to both the generator and the discriminator of the LcGAN during training.

COMPUTED TOMOGRAPHY (CT) CONDITIONAL IMAGE GENERATION DATA AUGMENTATION LESION SEGMENTATION

BigGAN-based Bayesian reconstruction of natural images from human brain activity

13 Mar 2020

In this study, we proposed a new GAN-based Bayesian visual reconstruction method (GAN-BVRM) that includes a classifier to decode categories from fMRI data, a pre-trained conditional generator to generate natural images of specified categories, and a set of encoding models and evaluator to evaluate generated images.

CONDITIONAL IMAGE GENERATION

Reconstructing the Noise Manifold for Image Denoising

11 Feb 2020

Deep Convolutional Neural Networks (CNNs) have been successfully used in many low-level vision problems like image denoising.

CONDITIONAL IMAGE GENERATION IMAGE DENOISING SUPER-RESOLUTION