Sketch-to-Image Translation
9 papers with code • 3 benchmarks • 4 datasets
Benchmarks
These leaderboards are used to track progress in Sketch-to-Image Translation
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COCO-Stuff
SketchyCOCO
Scribble
FS2K
Most implemented papers
Semantic Image Synthesis with Spatially-Adaptive Normalization
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
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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/EdgeGAN
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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
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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
We propose to use pretraining to boost general image-to-image translation.
MaskSketch: Unpaired Structure-guided Masked Image Generation
google-research/masksketch
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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
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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
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
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ICCV 2021
In this paper, we present DeepSIM, a generative model for conditional image manipulation based on a single image.
