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 2851–2900 of 6689 papers

TitleStatusHype
Adversarial Domain Prompt Tuning and Generation for Single Domain Generalization—0
Diffusion Prism: Enhancing Diversity and Morphology Consistency in Mask-to-Image Diffusion—0
Spherical Manifold Guided Diffusion Model for Panoramic Image GenerationCode0
CacheQuant: Comprehensively Accelerated Diffusion Models—0
Scaling Inference Time Compute for Diffusion Models—0
Hierarchical Vision-Language Alignment for Text-to-Image Generation via Diffusion Models—0
A4A: Adapter for Adapter Transfer via All-for-All Mapping for Cross-Architecture Models—0
TFCustom: Customized Image Generation with Time-Aware Frequency Feature Guidance—0
Devil is in the Detail: Towards Injecting Fine Details of Image Prompt in Image Generation via Conflict-free Guidance and Stratified Attention—0
Detect-and-Guide: Self-regulation of Diffusion Models for Safe Text-to-Image Generation via Guideline Token Optimization—0
Z-Magic: Zero-shot Multiple Attributes Guided Image Creator—0
Black Hole-Driven Identity Absorbing in Diffusion Models—0
Let's Verify and Reinforce Image Generation Step by Step—0
Multi-Group Proportional Representations for Text-to-Image Models—0
Beyond Text: Implementing Multimodal Large Language Model-Powered Multi-Agent Systems Using a No-Code Platform—0
Decouple-Then-Merge: Finetune Diffusion Models as Multi-Task Learning—0
GLASS: Guided Latent Slot Diffusion for Object-Centric Learning—0
Adaptive Non-Uniform Timestep Sampling for Accelerating Diffusion Model Training—0
Beyond Generation: A Diffusion-based Low-level Feature Extractor for Detecting AI-generated Images—0
Generative Zero-Shot Composed Image Retrieval—0
D^2iT: Dynamic Diffusion Transformer for Accurate Image GenerationCode0
Harnessing Global-Local Collaborative Adversarial Perturbation for Anti-Customization—0
Generalizable Object Keypoint Localization from Generative Priors—0
SKE-Layout: Spatial Knowledge Enhanced Layout Generation with LLMs—0
Adapting Text-to-Image Generation with Feature Difference Instruction for Generic Image Restoration—0
Unseen Visual Anomaly Generation—0
Regression Guided Strategy to Automated Facial Beauty Optimization through Image Synthesis—0
Learning Partonomic 3D Reconstruction from Image CollectionsCode0
FluxSpace: Disentangled Semantic Editing in Rectified Flow Models—0
Simpler Diffusion: 1.5 FID on ImageNet512 with Pixel-space Diffusion—0
One-Way Ticket: Time-Independent Unified Encoder for Distilling Text-to-Image Diffusion Models—0
Flowing from Words to Pixels: A Noise-Free Framework for Cross-Modality Evolution—0
Finding Local Diffusion Schrodinger Bridge using Kolmogorov-Arnold NetworkCode0
Patch Matters: Training-free Fine-grained Image Caption Enhancement via Local Perception—0
Yo'Chameleon: Personalized Vision and Language Generation—0
Towards Universal Dataset Distillation via Task-Driven Diffusion—0
Consistency Posterior Sampling for Diverse Image Synthesis—0
SmartSpatial: Enhancing the 3D Spatial Arrangement Capabilities of Stable Diffusion Models and Introducing a Novel 3D Spatial Evaluation Framework—0
Enhancing Early Diabetic Retinopathy Detection through Synthetic DR1 Image Generation: A StyleGAN3 Approach—0
Composing Parts for Expressive Object Generation—0
MC^2: Multi-concept Guidance for Customized Multi-concept GenerationCode0
EIDT-V: Exploiting Intersections in Diffusion Trajectories for Model-Agnostic, Zero-Shot, Training-Free Text-to-Video Generation—0
Token Pruning for Caching Better: 9 Times Acceleration on Stable Diffusion for FreeCode0
MLLM-as-a-Judge for Image Safety without Human Labeling—0
Text-to-Image GAN with Pretrained Representations—0
Latent Drifting in Diffusion Models for Counterfactual Medical Image Synthesis—0
PQD: Post-training Quantization for Efficient Diffusion Models—0
Prometheus: 3D-Aware Latent Diffusion Models for Feed-Forward Text-to-3D Scene Generation—0
Quantum Diffusion Model for Quark and Gluon Jet GenerationCode0
Diff4MMLiTS: Advanced Multimodal Liver Tumor Segmentation via Diffusion-Based Image Synthesis and Alignment—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