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 20262050 of 6689 papers

TitleStatusHype
SyncNoise: Geometrically Consistent Noise Prediction for Text-based 3D Scene Editing0
EvolvED: Evolutionary Embeddings to Understand the Generation Process of Diffusion Models0
Masked Generative Extractor for Synergistic Representation and 3D Generation of Point Clouds0
TSynD: Targeted Synthetic Data Generation for Enhanced Medical Image Classification0
FaceScore: Benchmarking and Enhancing Face Quality in Human GenerationCode2
EVALALIGN: Supervised Fine-Tuning Multimodal LLMs with Human-Aligned Data for Evaluating Text-to-Image ModelsCode1
Character-Adapter: Prompt-Guided Region Control for High-Fidelity Character CustomizationCode2
Prompt-Consistency Image Generation (PCIG): A Unified Framework Integrating LLMs, Knowledge Graphs, and Controllable Diffusion ModelsCode0
Repulsive Latent Score Distillation for Solving Inverse ProblemsCode0
ResMaster: Mastering High-Resolution Image Generation via Structural and Fine-Grained Guidance0
Beyond Thumbs Up/Down: Untangling Challenges of Fine-Grained Feedback for Text-to-Image Generation0
Repairing Catastrophic-Neglect in Text-to-Image Diffusion Models via Attention-Guided Feature EnhancementCode0
DreamBench++: A Human-Aligned Benchmark for Personalized Image GenerationCode2
EmoAttack: Emotion-to-Image Diffusion Models for Emotional Backdoor Generation0
Soft Masked Mamba Diffusion Model for CT to MRI ConversionCode2
Disability Representations: Finding Biases in Automatic Image Generation0
Latent diffusion models for parameterization and data assimilation of facies-based geomodels0
Backdooring Bias into Text-to-Image ModelsCode0
Holistic Evaluation for Interleaved Text-and-Image Generation0
Video Generation with Learned Action Prior0
Invertible Consistency Distillation for Text-Guided Image Editing in Around 7 Steps0
Consistency Models Made EasyCode3
CollaFuse: Collaborative Diffusion ModelsCode0
Fantastic Copyrighted Beasts and How (Not) to Generate ThemCode1
What's Next? Exploring Utilization, Challenges, and Future Directions of AI-Generated Image Tools in Graphic Design0
Show:102550
← PrevPage 82 of 268Next →

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