Image Generation

1918 papers with code • 85 benchmarks • 67 datasets

Image Generation (synthesis) is the task of generating new images from an existing dataset.

  • Unconditional generation refers to generating samples unconditionally from the dataset, i.e. $p(y)$
  • Conditional image generation (subtask) refers to generating samples conditionally from the dataset, based on a label, i.e. $p(y|x)$.

In this section, you can find state-of-the-art leaderboards for unconditional generation. For conditional generation, and other types of image generations, refer to the subtasks.

( Image credit: StyleGAN )

Libraries

Use these libraries to find Image Generation models and implementations

Self-Rectifying Diffusion Sampling with Perturbed-Attention Guidance

KU-CVLAB/Perturbed-Attention-Guidance 26 Mar 2024

These techniques are often not applicable in unconditional generation or in various downstream tasks such as image restoration.

55
26 Mar 2024

SDXS: Real-Time One-Step Latent Diffusion Models with Image Conditions

IDKiro/sdxs 25 Mar 2024

Recent advancements in diffusion models have positioned them at the forefront of image generation.

100
25 Mar 2024

Multi-Scale Texture Loss for CT denoising with GANs

francescodifeola/denotextureloss 25 Mar 2024

To grasp highly complex and non-linear textural relationships in the training process, this work presents a loss function that leverages the intrinsic multi-scale nature of the Gray-Level-Co-occurrence Matrix (GLCM).

0
25 Mar 2024

Long-CLIP: Unlocking the Long-Text Capability of CLIP

beichenzbc/long-clip 22 Mar 2024

Contrastive Language-Image Pre-training (CLIP) has been the cornerstone for zero-shot classification, text-image retrieval, and text-image generation by aligning image and text modalities.

105
22 Mar 2024

Generative Active Learning for Image Synthesis Personalization

zhangxulu1996/gal4personalization 22 Mar 2024

The primary challenge in conducting active learning on generative models lies in the open-ended nature of querying, which differs from the closed form of querying in discriminative models that typically target a single concept.

1
22 Mar 2024

Open-Vocabulary Attention Maps with Token Optimization for Semantic Segmentation in Diffusion Models

vpulab/ovam 21 Mar 2024

This approach limits the generation of segmentation masks derived from word tokens not contained in the text prompt.

13
21 Mar 2024

Diversity-aware Channel Pruning for StyleGAN Compression

jiwoogit/dcp-gan 20 Mar 2024

Specifically, by assessing channel importance based on their sensitivities to latent vector perturbations, our method enhances the diversity of samples in the compressed model.

6
20 Mar 2024

IIDM: Image-to-Image Diffusion Model for Semantic Image Synthesis

ader47/jittor-jieke-semantic_images_synthesis 20 Mar 2024

Semantic image synthesis aims to generate high-quality images given semantic conditions, i. e. segmentation masks and style reference images.

2
20 Mar 2024

Step-Calibrated Diffusion for Biomedical Optical Image Restoration

mlneurosurg/restorative_step-calibrated_diffusion 20 Mar 2024

Here, we present Restorative Step-Calibrated Diffusion (RSCD), an unpaired image restoration method that views the image restoration problem as completing the finishing steps of a diffusion-based image generation task.

1
20 Mar 2024

Towards Learning Contrast Kinetics with Multi-Condition Latent Diffusion Models

richardobi/ccnet 20 Mar 2024

Contrast agents in dynamic contrast enhanced magnetic resonance imaging allow to localize tumors and observe their contrast kinetics, which is essential for cancer characterization and respective treatment decision-making.

0
20 Mar 2024