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

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Showing 3551–3600 of 6689 papers

TitleStatusHype
Zero-shot Text-guided Infinite Image Synthesis with LLM guidance—0
I2AM: Interpreting Image-to-Image Latent Diffusion Models via Attribution Maps—0
Towards Understanding Unsafe Video GenerationCode0
Promptable Counterfactual Diffusion Model for Unified Brain Tumor Segmentation and Generation with MRIsCode0
Flatfish Disease Detection Based on Part Segmentation Approach and Disease Image Generation—0
How Control Information Influences Multilingual Text Image Generation and Editing?Code0
Subject-driven Text-to-Image Generation via Preference-based Reinforcement LearningCode0
Beta Sampling is All You Need: Efficient Image Generation Strategy for Diffusion Models using Stepwise Spectral Analysis—0
DiNO-Diffusion. Scaling Medical Diffusion via Self-Supervised Pre-Training—0
Zero-Shot Adaptation for Approximate Posterior Sampling of Diffusion Models in Inverse ProblemsCode0
Efficient Training with Denoised Neural Weights—0
Mask-guided cross-image attention for zero-shot in-silico histopathologic image generation with a diffusion model—0
Domain Generalization for 6D Pose Estimation Through NeRF-based Image Synthesis—0
OPa-Ma: Text Guided Mamba for 360-degree Image Out-painting—0
Addressing Image Hallucination in Text-to-Image Generation through Factual Image Retrieval—0
Optical Diffusion Models for Image Generation—0
Physics-Inspired Generative Models in Medical Imaging: A Review—0
A Survey of Defenses against AI-generated Visual Media: Detection, Disruption, and Authentication—0
ContextualStory: Consistent Visual Storytelling with Spatially-Enhanced and Storyline ContextCode0
Layout-and-Retouch: A Dual-stage Framework for Improving Diversity in Personalized Image Generation—0
FairyLandAI: Personalized Fairy Tales utilizing ChatGPT and DALLE-3—0
Machine Apophenia: The Kaleidoscopic Generation of Architectural Images—0
Surgical Text-to-Image Generation—0
E2VIDiff: Perceptual Events-to-Video Reconstruction using Diffusion Priors—0
Enriching Information and Preserving Semantic Consistency in Expanding Curvilinear Object Segmentation DatasetsCode0
Boosting Medical Image Synthesis via Registration-guided Consistency and Disentanglement Learning—0
Sketch-Guided Scene Image Generation—0
Accelerating Mobile Edge Generation (MEG) by Constrained Learning—0
Few-Shot Image Generation by Conditional Relaxing Diffusion Inversion—0
Spanish TrOCR: Leveraging Transfer Learning for Language AdaptationCode0
MMIS: Multimodal Dataset for Interior Scene Visual Generation and Recognition—0
GenArtist: Multimodal LLM as an Agent for Unified Image Generation and Editing—0
JeDi: Joint-Image Diffusion Models for Finetuning-Free Personalized Text-to-Image Generation—0
MobilePortrait: Real-Time One-Shot Neural Head Avatars on Mobile Devices—0
Layered Diffusion Model for One-Shot High Resolution Text-to-Image Synthesis—0
Rethinking Image Skip Connections in StyleGAN2—0
An Improved Method for Personalizing Diffusion Models—0
Multi-scale Conditional Generative Modeling for Microscopic Image Restoration—0
Enhancing Label-efficient Medical Image Segmentation with Text-guided Diffusion Models—0
PROUD: PaRetO-gUided Diffusion Model for Multi-objective GenerationCode0
DiCTI: Diffusion-based Clothing Designer via Text-guided Input—0
Medical Image Fusion for High-Level Analysis: A Mutual Enhancement Framework for Unaligned PAT and MRICode0
Model Collapse in the Self-Consuming Chain of Diffusion Finetuning: A Novel Perspective from Quantitative Trait Modeling—0
Lateralization LoRA: Interleaved Instruction Tuning with Modality-Specialized Adaptations—0
Representation learning with CGAN for casual inference—0
BACON: Improving Clarity of Image Captions via Bag-of-Concept Graphs—0
Mobile Edge Generation-Enabled Digital Twin: Architecture Design and Research OpportunitiesCode0
SwiftDiffusion: Efficient Diffusion Model Serving with Add-on Modules—0
UltraPixel: Advancing Ultra-High-Resolution Image Synthesis to New Peaks—0
Label-free Neural Semantic Image Synthesis—0
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All datasetsImageNet 256x256CIFAR-10ImageNet 64x64ImageNet 512x512FFHQ 256 x 256CelebA 64x64ImageNet 32x32LSUN Bedroom 256 x 256STL-10LSUN Churches 256 x 256ImageNet 128x128FFHQ 1024 x 1024

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Improved DDPMFID12.3—Unverified
2ADMFID11.84—Unverified
3BigGAN-deepFID8.1—Unverified
4Polarity-BigGANFID6.82—Unverified
5VQGAN+Transformer (k=mixed, p=1.0, a=0.005)FID6.59—Unverified
6MaskGITFID6.18—Unverified
7VQGAN+Transformer (k=600, p=1.0, a=0.05)FID5.2—Unverified
8CDMFID4.88—Unverified
9ADM-GFID4.59—Unverified
10RINFID4.51—Unverified
#ModelMetricClaimedVerifiedStatus
1PresGANFID52.2—Unverified
2RESFLOWFID48.29—Unverified
3Residual FlowFID46.37—Unverified
4GLF+perceptual loss (ours)FID44.6—Unverified
5ProdPoly no activation functionsFID40.45—Unverified
6ProdPoly no activation functionsFID36.77—Unverified
7ACGANFID35.47—Unverified
8DenseFlow-74-10FID34.9—Unverified
9NVAE w/ flowFID32.53—Unverified
10QSNGANFID31.97—Unverified
#ModelMetricClaimedVerifiedStatus
1GLIDE + CLSFID30.87—Unverified
2GLIDE + CLIPFID30.46—Unverified
3GLIDE + CLS-FREEFID29.22—Unverified
4GLIDE + CLIP + CLS + CLS-FREEFID29.18—Unverified
5PGMGANFID21.73—Unverified
6CLR-GANFID20.27—Unverified
7FMFID14.45—Unverified
8CT (Direct Generation, NFE=1)FID13—Unverified
9CT (Direct Generation, NFE=2)FID11.1—Unverified
10GLIDE +CLSKID7.95—Unverified