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 101–150 of 6689 papers

TitleStatusHype
MAMBO: High-Resolution Generative Approach for Mammography Images—0
Re-Thinking the Automatic Evaluation of Image-Text Alignment in Text-to-Image Models—0
Diffuse and Disperse: Image Generation with Representation Regularization—0
Autoregressive Semantic Visual Reconstruction Helps VLMs Understand BetterCode2
SkipVAR: Accelerating Visual Autoregressive Modeling via Adaptive Frequency-Aware SkippingCode0
Diffusion Counterfactual Generation with Semantic AbductionCode0
MADFormer: Mixed Autoregressive and Diffusion Transformers for Continuous Image Generation—0
VIVAT: Virtuous Improving VAE Training through Artifact Mitigation—0
Explore the vulnerability of black-box models via diffusion models—0
APTOS-2024 challenge report: Generation of synthetic 3D OCT images from fundus photographs—0
Diffuse Everything: Multimodal Diffusion Models on Arbitrary State SpacesCode1
OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image GenerationCode2
Highly Compressed Tokenizer Can Generate Without TrainingCode3
A Comprehensive Study of Decoder-Only LLMs for Text-to-Image Generation—0
AR-RAG: Autoregressive Retrieval Augmentation for Image GenerationCode0
Training-Free Identity Preservation in Stylized Image Generation Using Diffusion Models—0
ResPF: Residual Poisson Flow for Efficient and Physically Consistent Sparse-View CT Reconstruction—0
Noise Consistency Regularization for Improved Subject-Driven Image Synthesis—0
Peer-Ranked Precision: Creating a Foundational Dataset for Fine-Tuning Vision Models from DataSeeds' Annotated ImageryCode0
PixCell: A generative foundation model for digital histopathology images—0
Aligning Latent Spaces with Flow Priors—0
ContentV: Efficient Training of Video Generation Models with Limited Compute—0
AliTok: Towards Sequence Modeling Alignment between Tokenizer and Autoregressive ModelCode2
Improving AI-generated music with user-guided training—0
Invisible Backdoor Triggers in Image Editing Model via Deep WatermarkingCode0
ControlThinker: Unveiling Latent Semantics for Controllable Image Generation through Visual ReasoningCode0
Backbone Augmented Training for Adaptations—0
Is Perturbation-Based Image Protection Disruptive to Image Editing?—0
HMAR: Efficient Hierarchical Masked Auto-Regressive Image Generation—0
Solving Inverse Problems with FLAIR—0
Hyperspectral Image Generation with Unmixing Guided Diffusion Model—0
Flexiffusion: Training-Free Segment-Wise Neural Architecture Search for Efficient Diffusion Models—0
UniWorld-V1: High-Resolution Semantic Encoders for Unified Visual Understanding and GenerationCode4
Rethinking Machine Unlearning in Image Generation ModelsCode1
Absorb and Converge: Provable Convergence Guarantee for Absorbing Discrete Diffusion Models—0
PointT2I: LLM-based text-to-image generation via keypoints—0
Ultra-High-Resolution Image Synthesis: Data, Method and EvaluationCode3
Unlocking Aha Moments via Reinforcement Learning: Advancing Collaborative Visual Comprehension and Generation—0
A 2-Stage Model for Vehicle Class and Orientation Detection with Photo-Realistic Image Generation—0
Psi-Sampler: Initial Particle Sampling for SMC-Based Inference-Time Reward Alignment in Score Models—0
TaxaDiffusion: Progressively Trained Diffusion Model for Fine-Grained Species GenerationCode0
Image Generation from Contextually-Contradictory Prompts—0
OG-VLA: 3D-Aware Vision Language Action Model via Orthographic Image Generation—0
Latent Wavelet Diffusion: Enabling 4K Image Synthesis for Free—0
ArtiScene: Language-Driven Artistic 3D Scene Generation Through Image Intermediary—0
ComposeAnything: Composite Object Priors for Text-to-Image Generation—0
GenSpace: Benchmarking Spatially-Aware Image Generation—0
Graph Flow Matching: Enhancing Image Generation with Neighbor-Aware Flow Fields—0
Draw ALL Your Imagine: A Holistic Benchmark and Agent Framework for Complex Instruction-based Image GenerationCode1
Category-aware EEG image generation based on wavelet transform and contrast semantic lossCode0
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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