SOTAVerified

Image Generation

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 )

Papers

Showing 31263150 of 6689 papers

TitleStatusHype
Reconciling Semantic Controllability and Diversity for Remote Sensing Image Synthesis with Hybrid Semantic Embedding0
Learning Modality-Aware Representations: Adaptive Group-wise Interaction Network for Multimodal MRI SynthesisCode0
Foundation Cures Personalization: Recovering Facial Personalized Models' Prompt Consistency0
Exploiting Watermark-Based Defense Mechanisms in Text-to-Image Diffusion Models for Unauthorized Data Usage0
Unsupervised Multi-view UAV Image Geo-localization via Iterative Rendering0
ComfyGI: Automatic Improvement of Image Generation Workflows0
Edge-Cloud Routing for Text-to-Image Model with Token-Level Multi-Metric Prediction0
Safety Without Semantic Disruptions: Editing-free Safe Image Generation via Context-preserving Dual Latent Reconstruction0
Dealing with Synthetic Data Contamination in Online Continual LearningCode0
GalaxyEdit: Large-Scale Image Editing Dataset with Enhanced Diffusion Adapter0
Text Embedding is Not All You Need: Attention Control for Text-to-Image Semantic Alignment with Text Self-Attention Maps0
CopyrightMeter: Revisiting Copyright Protection in Text-to-image Models0
CCIS-Diff: A Generative Model with Stable Diffusion Prior for Controlled Colonoscopy Image Synthesis0
Adaptively Controllable Diffusion Model for Efficient Conditional Image Generation0
Frequency-Aware Guidance for Blind Image Restoration via Diffusion Models0
Constant Rate Schedule: Constant-Rate Distributional Change for Efficient Training and Sampling in Diffusion Models0
Enhancing Low Dose Computed Tomography Images Using Consistency Training Techniques0
Zoomed In, Diffused Out: Towards Local Degradation-Aware Multi-Diffusion for Extreme Image Super-ResolutionCode0
Cascaded Diffusion Models for 2D and 3D Microscopy Image Synthesis to Enhance Cell SegmentationCode0
Decoupling Training-Free Guided Diffusion by ADMM0
BeautyBank: Encoding Facial Makeup in Latent Space0
A Modular Open Source Framework for Genomic Variant Calling0
Conceptwm: A Diffusion Model Watermark for Concept Protection0
Time Step Generating: A Universal Synthesized Deepfake Image DetectorCode0
Enhanced Anime Image Generation Using USE-CMHSA-GAN0
Show:102550
← PrevPage 126 of 268Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Improved DDPMFID12.3Unverified
2ADMFID11.84Unverified
3BigGAN-deepFID8.1Unverified
4Polarity-BigGANFID6.82Unverified
5VQGAN+Transformer (k=mixed, p=1.0, a=0.005)FID6.59Unverified
6MaskGITFID6.18Unverified
7VQGAN+Transformer (k=600, p=1.0, a=0.05)FID5.2Unverified
8CDMFID4.88Unverified
9ADM-GFID4.59Unverified
10RINFID4.51Unverified
#ModelMetricClaimedVerifiedStatus
1PresGANFID52.2Unverified
2RESFLOWFID48.29Unverified
3Residual FlowFID46.37Unverified
4GLF+perceptual loss (ours)FID44.6Unverified
5ProdPoly no activation functionsFID40.45Unverified
6ProdPoly no activation functionsFID36.77Unverified
7ACGANFID35.47Unverified
8DenseFlow-74-10FID34.9Unverified
9NVAE w/ flowFID32.53Unverified
10QSNGANFID31.97Unverified
#ModelMetricClaimedVerifiedStatus
1GLIDE + CLSFID30.87Unverified
2GLIDE + CLIPFID30.46Unverified
3GLIDE + CLS-FREEFID29.22Unverified
4GLIDE + CLIP + CLS + CLS-FREEFID29.18Unverified
5PGMGANFID21.73Unverified
6CLR-GANFID20.27Unverified
7FMFID14.45Unverified
8CT (Direct Generation, NFE=1)FID13Unverified
9CT (Direct Generation, NFE=2)FID11.1Unverified
10GLIDE +CLSKID7.95Unverified