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 36263650 of 6689 papers

TitleStatusHype
Facial Image Generation from Bangla Textual Description using DCGAN and Bangla FastTextCode0
DreamIdentity: Improved Editability for Efficient Face-identity Preserved Image Generation0
AIGCIQA2023: A Large-scale Image Quality Assessment Database for AI Generated Images: from the Perspectives of Quality, Authenticity and CorrespondenceCode1
Practical and Asymptotically Exact Conditional Sampling in Diffusion ModelsCode1
Counting Guidance for High Fidelity Text-to-Image Synthesis0
Stay on topic with Classifier-Free Guidance0
DreamDiffusion: Generating High-Quality Images from Brain EEG SignalsCode2
CLIPAG: Towards Generator-Free Text-to-Image Generation0
NaturalInversion: Data-Free Image Synthesis Improving Real-World ConsistencyCode1
Semi-supervised Multimodal Representation Learning through a Global WorkspaceCode0
Approximated Prompt Tuning for Vision-Language Pre-trained Models0
Text-Anchored Score Composition: Tackling Condition Misalignment in Text-to-Image Diffusion ModelsCode1
A-STAR: Test-time Attention Segregation and Retention for Text-to-image Synthesis0
Localized Text-to-Image Generation for Free via Cross Attention Control0
Fuzzy-Conditioned Diffusion and Diffusion Projection Attention Applied to Facial Image CorrectionCode1
A Simple and Effective Baseline for Attentional Generative Adversarial NetworksCode1
DomainStudio: Fine-Tuning Diffusion Models for Domain-Driven Image Generation using Limited DataCode0
UAlberta at SemEval-2023 Task 1: Context Augmentation and Translation for Multilingual Visual Word Sense DisambiguationCode0
Zero-shot spatial layout conditioning for text-to-image diffusion models0
Simultaneous Image-to-Zero and Zero-to-Noise: Diffusion Models with Analytical Image AttenuationCode1
A New Paradigm for Generative Adversarial Networks based on Randomized Decision RulesCode0
DiffInfinite: Large Mask-Image Synthesis via Parallel Random Patch Diffusion in HistopathologyCode1
Directional diffusion models for graph representation learning0
DreamEdit: Subject-driven Image Editing0
Benchmarking and Analyzing 3D-aware Image Synthesis with a Modularized CodebaseCode1
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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