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 28762900 of 6689 papers

TitleStatusHype
Attributing Fake Images to GANs: Learning and Analyzing GAN FingerprintsCode0
Laplacian-Steered Neural Style TransferCode0
FakePolisher: Making DeepFakes More Detection-Evasive by Shallow ReconstructionCode0
Language-based Colorization of Scene SketchesCode0
Language Guided Adversarial PurificationCode0
LAViTeR: Learning Aligned Visual and Textual Representations Assisted by Image and Caption GenerationCode0
Long Tail Image Generation Through Feature Space Augmentation and Iterated LearningCode0
Kvasir-VQA: A Text-Image Pair GI Tract DatasetCode0
Knowledge-Aware Artifact Image Synthesis with LLM-Enhanced Prompting and Multi-Source SupervisionCode0
Fair Generative Modeling via Weak SupervisionCode0
Kosmos-G: Generating Images in Context with Multimodal Large Language ModelsCode0
Kernel Mean Matching for Content Addressability of GANsCode0
Context-Aware Compilation of DNN Training Pipelines across Edge and CloudCode0
Tell, Draw, and Repeat: Generating and Modifying Images Based on Continual Linguistic InstructionCode0
Guided and Variance-Corrected Fusion with One-shot Style Alignment for Large-Content Image GenerationCode0
LAION-5B: An open large-scale dataset for training next generation image-text modelsCode0
Attribute2Image: Conditional Image Generation from Visual AttributesCode0
An End-to-End Model for Photo-Sharing Multi-modal Dialogue GenerationCode0
Joint Learning of Neural Networks via Iterative Reweighted Least SquaresCode0
Facial Image Generation from Bangla Textual Description using DCGAN and Bangla FastTextCode0
Learning from Mistakes: Iterative Prompt Relabeling for Text-to-Image Diffusion Model TrainingCode0
Iterative Neural Autoregressive Distribution Estimator NADE-kCode0
Iterative Neural Autoregressive Distribution Estimator (NADE-k)Code0
IterInv: Iterative Inversion for Pixel-Level T2I ModelsCode0
Gotta Adapt 'Em All: Joint Pixel and Feature-Level Domain Adaptation for Recognition in the WildCode0
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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