Sketch-to-Image Translation

9 papers with code • 3 benchmarks • 5 datasets

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Most implemented papers

Semantic Image Synthesis with Spatially-Adaptive Normalization

NVlabs/SPADE CVPR 2019

Previous methods directly feed the semantic layout as input to the deep network, which is then processed through stacks of convolution, normalization, and nonlinearity layers.

High-Resolution Image Synthesis and Semantic Manipulation with Conditional GANs

NVIDIA/pix2pixHD CVPR 2018

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

SketchyCOCO: Image Generation from Freehand Scene Sketches

sysu-imsl/SketchyCOCO CVPR 2020

We introduce the first method for automatic image generation from scene-level freehand sketches.

Adversarial Open Domain Adaptation for Sketch-to-Photo Synthesis

Mukosame/AODA 12 Apr 2021

In this paper, we explore open-domain sketch-to-photo translation, which aims to synthesize a realistic photo from a freehand sketch with its class label, even if the sketches of that class are missing in the training data.

Pretraining is All You Need for Image-to-Image Translation

PITI-Synthesis/PITI 25 May 2022

We propose to use pretraining to boost general image-to-image translation.

MaskSketch: Unpaired Structure-guided Masked Image Generation

google-research/masksketch CVPR 2023

We show that intermediate self-attention maps of a masked generative transformer encode important structural information of the input image, such as scene layout and object shape, and we propose a novel sampling method based on this observation to enable structure-guided generation.

Interactive Sketch & Fill: Multiclass Sketch-to-Image Translation

arnabgho/iSketchNFill ICCV 2019

We propose an interactive GAN-based sketch-to-image translation method that helps novice users create images of simple objects.

Image Shape Manipulation from a Single Augmented Training Sample

eliahuhorwitz/DeepSIM 2 Jul 2020

In this paper, we present DeepSIM, a generative model for conditional image manipulation based on a single image.

Image Shape Manipulation from a Single Augmented Training Sample

eliahuhorwitz/DeepSIM ICCV 2021

In this paper, we present DeepSIM, a generative model for conditional image manipulation based on a single image.