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 1701–1750 of 6689 papers

TitleStatusHype
Attribute-guided image generation from layoutCode1
Probabilistic AutoencoderCode1
Contextual Convolutional Neural NetworksCode1
Attribute Group Editing for Reliable Few-shot Image GenerationCode1
FunkNN: Neural Interpolation for Functional GenerationCode1
FuseDream: Training-Free Text-to-Image Generation with Improved CLIP+GAN Space OptimizationCode1
Fully Spiking Denoising Diffusion Implicit ModelsCode1
Prompt-Agnostic Adversarial Perturbation for Customized Diffusion ModelsCode1
Context-Aware Layout to Image Generation with Enhanced Object AppearanceCode1
Capability-aware Prompt Reformulation Learning for Text-to-Image GenerationCode1
Fully Spiking Variational AutoencoderCode1
E2NeRF: Event Enhanced Neural Radiance Fields from Blurry ImagesCode1
Diffusion Probabilistic Modeling for Video GenerationCode1
Fully automatic computer-aided mass detection and segmentation via pseudo-color mammograms and Mask R-CNNCode1
AITTI: Learning Adaptive Inclusive Token for Text-to-Image GenerationCode1
Learning to Generate Levels From NothingCode1
Fundamental Benefit of Alternating Updates in Minimax OptimizationCode1
Fuzzy-Conditioned Diffusion and Diffusion Projection Attention Applied to Facial Image CorrectionCode1
Causal Inference via Style Transfer for Out-of-distribution GeneralisationCode1
From Face to Natural Image: Learning Real Degradation for Blind Image Super-ResolutionCode1
CE-VAE: Capsule Enhanced Variational AutoEncoder for Underwater Image EnhancementCode1
PTQ4DiT: Post-training Quantization for Diffusion TransformersCode1
AttnGAN: Fine-Grained Text to Image Generation with Attentional Generative Adversarial NetworksCode1
Diffusion Self-Guidance for Controllable Image GenerationCode1
From Image to Imuge: Immunized Image GenerationCode1
Full-Glow: Fully conditional Glow for more realistic image generationCode1
Content-Aware GAN CompressionCode1
3D-aware Image Synthesis via Learning Structural and Textural RepresentationsCode1
Frequency Domain Image Translation: More Photo-realistic, Better Identity-preservingCode1
Freestyle Layout-to-Image SynthesisCode1
FBSDiff: Plug-and-Play Frequency Band Substitution of Diffusion Features for Highly Controllable Text-Driven Image TranslationCode1
DiffX: Guide Your Layout to Cross-Modal Generative ModelingCode1
Realistic Evaluation of Model Merging for Compositional GeneralizationCode1
DiG-IN: Diffusion Guidance for Investigating Networks - Uncovering Classifier Differences Neuron Visualisations and Visual Counterfactual ExplanationsCode1
DIG In: Evaluating Disparities in Image Generations with Indicators for Geographic DiversityCode1
Adversarial Generation of Continuous ImagesCode1
Attentive Normalization for Conditional Image GenerationCode1
Freeze the Discriminator: a Simple Baseline for Fine-Tuning GANsCode1
Frido: Feature Pyramid Diffusion for Complex Scene Image SynthesisCode1
CoCosNet v2: Full-Resolution Correspondence Learning for Image TranslationCode1
Redefining Temporal Modeling in Video Diffusion: The Vectorized Timestep ApproachCode1
Frame Interpolation with Consecutive Brownian Bridge DiffusionCode1
FreCaS: Efficient Higher-Resolution Image Generation via Frequency-aware Cascaded SamplingCode1
ConsistNet: Enforcing 3D Consistency for Multi-view Images DiffusionCode1
FPGAN-Control: A Controllable Fingerprint Generator for Training with Synthetic DataCode1
Refining Generative Process with Discriminator Guidance in Score-based Diffusion ModelsCode1
DiMSUM: Diffusion Mamba -- A Scalable and Unified Spatial-Frequency Method for Image GenerationCode1
Applying Guidance in a Limited Interval Improves Sample and Distribution Quality in Diffusion ModelsCode1
Forward-only Diffusion Probabilistic ModelsCode1
AI Illustrator: Translating Raw Descriptions into Images by Prompt-based Cross-Modal GenerationCode1
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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