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 6051–6100 of 6689 papers

TitleStatusHype
PopAlign: Population-Level Alignment for Fair Text-to-Image GenerationCode0
Invisible Backdoor Triggers in Image Editing Model via Deep WatermarkingCode0
RPGAN: GANs Interpretability via Random RoutingCode0
Beta-Sigma VAE: Separating beta and decoder variance in Gaussian variational autoencoderCode0
A Survey on fMRI-based Brain Decoding for Reconstructing Multimodal StimuliCode0
RPGAN: random paths as a latent space for GAN interpretabilityCode0
A Patch-Based Algorithm for Diverse and High Fidelity Single Image GenerationCode0
CusConcept: Customized Visual Concept Decomposition with Diffusion ModelsCode0
A Conditional Denoising Diffusion Probabilistic Model for Radio Interferometric Image ReconstructionCode0
SSPP-DAN: Deep Domain Adaptation Network for Face Recognition with Single Sample Per PersonCode0
SynthText3D: Synthesizing Scene Text Images from 3D Virtual WorldsCode0
Discriminator Rejection SamplingCode0
Follow the Flow: On Information Flow Across Textual Tokens in Text-to-Image ModelsCode0
RusCode: Russian Cultural Code Benchmark for Text-to-Image GenerationCode0
Structured Uncertainty in the Observation Space of Variational AutoencodersCode0
MultiFusion: Fusing Pre-Trained Models for Multi-Lingual, Multi-Modal Image GenerationCode0
Multi-Granularity Denoising and Bidirectional Alignment for Weakly Supervised Semantic SegmentationCode0
Towards Label-Efficient Human Matting: A Simple Baseline for Weakly Semi-Supervised Trimap-Free Human MattingCode0
VersusDebias: Universal Zero-Shot Debiasing for Text-to-Image Models via SLM-Based Prompt Engineering and Generative AdversaryCode0
Zero-Shot Visual Concept Blending Without Text GuidanceCode0
KPE: Keypoint Pose Encoding for Transformer-based Image GenerationCode0
Pose Guided Person Image GenerationCode0
Forensic Iris Image SynthesisCode0
FoREST: Frame of Reference Evaluation in Spatial Reasoning TasksCode0
Multilingual Text-to-Image Generation Magnifies Gender Stereotypes and Prompt Engineering May Not Help YouCode0
Efficient Gradient Flows in Sliced-Wasserstein SpaceCode0
Pose Invariant Person Re-Identification using Robust Pose-transformation GANCode0
S2P: State-conditioned Image Synthesis for Data Augmentation in Offline Reinforcement LearningCode0
Diffusion Models with Deterministic Normalizing Flow PriorsCode0
Semantic Object Accuracy for Generative Text-to-Image SynthesisCode0
SWA-LDM: Toward Stealthy Watermarks for Latent Diffusion ModelsCode0
BendVLM: Test-Time Debiasing of Vision-Language EmbeddingsCode0
Iterative Neural Autoregressive Distribution Estimator NADE-kCode0
Benchmarking Generative Latent Variable Models for SpeechCode0
FP4DiT: Towards Effective Floating Point Quantization for Diffusion TransformersCode0
Iterative Neural Autoregressive Distribution Estimator (NADE-k)Code0
FPQVAR: Floating Point Quantization for Visual Autoregressive Model with FPGA Hardware Co-designCode0
Multimodal Benchmarking and Recommendation of Text-to-Image Generation ModelsCode0
Stabilizing Training of Generative Adversarial Networks through RegularizationCode0
Learning from Mistakes: Iterative Prompt Relabeling for Text-to-Image Diffusion Model TrainingCode0
DivTrackee versus DynTracker: Promoting Diversity in Anti-Facial Recognition against Dynamic FR StrategyCode0
IterInv: Iterative Inversion for Pixel-Level T2I ModelsCode0
Posterior Sampling Based on Gradient Flows of the MMD with Negative Distance KernelCode0
Towards More Accurate Personalized Image Generation: Addressing Overfitting and Evaluation BiasCode0
Safeguarding Text-to-Image Generation via Inference-Time Prompt-Noise OptimizationCode0
DiffLoss: unleashing diffusion model as constraint for training image restoration networkCode0
Multi-modal Generation via Cross-Modal In-Context LearningCode0
BEGAN: Boundary Equilibrium Generative Adversarial NetworksCode0
Towards Improving the Generation Quality of Autoregressive Slot VAEsCode0
Connecting Vision and Language with Localized NarrativesCode0
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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