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 2951–3000 of 6689 papers

TitleStatusHype
ArtAug: Enhancing Text-to-Image Generation through Synthesis-Understanding InteractionCode0
Posterior Mean Matching: Generative Modeling through Online Bayesian Inference—0
Numerical Pruning for Efficient Autoregressive Models—0
Guided and Variance-Corrected Fusion with One-shot Style Alignment for Large-Content Image GenerationCode0
3D MedDiffusion: A 3D Medical Diffusion Model for Controllable and High-quality Medical Image Generation—0
Prompt Augmentation for Self-supervised Text-guided Image Manipulation—0
F-Bench: Rethinking Human Preference Evaluation Metrics for Benchmarking Face Generation, Customization, and Restoration—0
Consistent Diffusion: Denoising Diffusion Model with Data-Consistent Training for Image Restoration—0
Unsupervised Region-Based Image Editing of Denoising Diffusion Models—0
Stable Diffusion is a Natural Cross-Modal Decoder for Layered AI-generated Image Compression—0
Efficient Scaling of Diffusion Transformers for Text-to-Image Generation—0
VersaGen: Unleashing Versatile Visual Control for Text-to-Image SynthesisCode0
LineArt: A Knowledge-guided Training-free High-quality Appearance Transfer for Design Drawing with Diffusion Model—0
A LoRA is Worth a Thousand Pictures—0
You Only Submit One Image to Find the Most Suitable Generative Model—0
FedCAR: Cross-client Adaptive Re-weighting for Generative Models in Federated LearningCode0
Nearly Zero-Cost Protection Against Mimicry by Personalized Diffusion Models—0
OmniPrism: Learning Disentangled Visual Concept for Image Generation—0
Provably Secure Robust Image Steganography via Cross-Modal Error Correction—0
Grassmannian Geometry Meets Dynamic Mode Decomposition in DMD-GEN: A New Metric for Mode Collapse in Time Series Generative Models—0
GenLit: Reformulating Single-Image Relighting as Video Generation—0
Plug-and-Play Priors as a Score-Based MethodCode0
Unbiased General Annotated Dataset Generation—0
Progressive Compression with Universally Quantized Diffusion Models—0
Efficient Generative Modeling with Residual Vector Quantization-Based Tokens—0
OP-LoRA: The Blessing of Dimensionality—0
SnapGen-V: Generating a Five-Second Video within Five Seconds on a Mobile Device—0
SafetyDPO: Scalable Safety Alignment for Text-to-Image Generation—0
EasyRef: Omni-Generalized Group Image Reference for Diffusion Models via Multimodal LLM—0
RAD: Region-Aware Diffusion Models for Image Inpainting—0
Vision-Language Models Represent Darker-Skinned Black Individuals as More Homogeneous than Lighter-Skinned Black Individuals—0
Are Conditional Latent Diffusion Models Effective for Image Restoration?—0
ViUniT: Visual Unit Tests for More Robust Visual Programming—0
Spectral Image Tokenizer—0
From Noise to Nuance: Advances in Deep Generative Image Models—0
FluxSpace: Disentangled Semantic Editing in Rectified Flow Transformers—0
LoRACLR: Contrastive Adaptation for Customization of Diffusion Models—0
Multimodal Approaches to Fair Image Classification: An Ethical Perspective—0
InvDiff: Invariant Guidance for Bias Mitigation in Diffusion ModelsCode0
CC-Diff: Enhancing Contextual Coherence in Remote Sensing Image Synthesis—0
Unlocking Visual Secrets: Inverting Features with Diffusion Priors for Image Reconstruction—0
GPTDrawer: Enhancing Visual Synthesis through ChatGPT—0
Seeing Syntax: Uncovering Syntactic Learning Limitations in Vision-Language Models—0
Generative Zoo—0
Generative Modeling with Explicit MemoryCode0
Analyzing and Improving Model Collapse in Rectified Flow Models—0
Multimodal Latent Language Modeling with Next-Token DiffusionCode0
AsyncDSB: Schedule-Asynchronous Diffusion Schrödinger Bridge for Image Inpainting—0
CAP: Evaluation of Persuasive and Creative Image GenerationCode0
Moderating the Generalization of Score-based Generative Model—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