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 20762100 of 6689 papers

TitleStatusHype
ControlVAR: Exploring Controllable Visual Autoregressive ModelingCode2
Toffee: Efficient Million-Scale Dataset Construction for Subject-Driven Text-to-Image Generation0
Understanding Hallucinations in Diffusion Models through Mode InterpolationCode2
StableMaterials: Enhancing Diversity in Material Generation via Semi-Supervised Learning0
An Image is Worth More Than 16x16 Patches: Exploring Transformers on Individual Pixels0
Batch-Instructed Gradient for Prompt Evolution:Systematic Prompt Optimization for Enhanced Text-to-Image SynthesisCode0
Alleviating Distortion in Image Generation via Multi-Resolution Diffusion Models and Time-Dependent Layer NormalizationCode1
EMMA: Your Text-to-Image Diffusion Model Can Secretly Accept Multi-Modal PromptsCode5
TC-Bench: Benchmarking Temporal Compositionality in Text-to-Video and Image-to-Video GenerationCode1
WMAdapter: Adding WaterMark Control to Latent Diffusion Models0
Words Worth a Thousand Pictures: Measuring and Understanding Perceptual Variability in Text-to-Image Generation0
FontStudio: Shape-Adaptive Diffusion Model for Coherent and Consistent Font Effect Generation0
DiTFastAttn: Attention Compression for Diffusion Transformer Models0
VisionLLM v2: An End-to-End Generalist Multimodal Large Language Model for Hundreds of Vision-Language TasksCode5
What If We Recaption Billions of Web Images with LLaMA-3?0
Understanding and Mitigating Compositional Issues in Text-to-Image Generative ModelsCode0
CFG++: Manifold-constrained Classifier Free Guidance for Diffusion ModelsCode1
Diffusion Soup: Model Merging for Text-to-Image Diffusion Models0
Progress Towards Decoding Visual Imagery via fNIRS0
Image and Video Tokenization with Binary Spherical QuantizationCode3
An Image is Worth 32 Tokens for Reconstruction and GenerationCode3
Image Textualization: An Automatic Framework for Creating Accurate and Detailed Image DescriptionsCode2
SPIN: Spacecraft Imagery for NavigationCode1
Beware of Aliases -- Signal Preservation is Crucial for Robust Image Restoration0
Understanding Visual Concepts Across ModelsCode0
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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