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 3301–3350 of 6689 papers

TitleStatusHype
Decouple-Then-Merge: Towards Better Training for Diffusion Models—0
G2D2: Gradient-guided Discrete Diffusion for image inverse problem solving—0
Learning AND-OR Templates for Professional Photograph Parsing and Guidance—0
Sparse Repellency for Shielded Generation in Text-to-image Diffusion Models—0
Generative Portrait Shadow Removal—0
TextureMeDefect: LLM-based Defect Texture Generation for Railway Components on Mobile Devices—0
HERO: Human-Feedback Efficient Reinforcement Learning for Online Diffusion Model Finetuning—0
OmniBooth: Learning Latent Control for Image Synthesis with Multi-modal Instruction—0
Empowering Backbone Models for Visual Text Generation with Input Granularity Control and Glyph-Aware Training—0
Disentangling Regional Primitives for Image Generation—0
Noise Crystallization and Liquid Noise: Zero-shot Video Generation using Image Diffusion Models—0
Lane Detection System for Driver Assistance in Vehicles—0
Test-Time Adaptation for Keypoint-Based Spacecraft Pose Estimation Based on Predicted-View SynthesisCode0
Accelerating Diffusion Models with One-to-Many Knowledge Distillation—0
Images Speak Volumes: User-Centric Assessment of Image Generation for Accessible CommunicationCode0
Tuning Timestep-Distilled Diffusion Model Using Pairwise Sample Optimization—0
Chain-of-Jailbreak Attack for Image Generation Models via Editing Step by Step—0
Uncovering Regional Defaults from Photorealistic Forests in Text-to-Image Generation with DALL-E 2—0
Grounded Answers for Multi-agent Decision-making Problem through Generative World Model—0
Plug-and-Play Controllable Generation for Discrete Masked Models—0
Event-Customized Image Generation—0
SteerDiff: Steering towards Safe Text-to-Image Diffusion Models—0
Revealing the Unseen: Guiding Personalized Diffusion Models to Expose Training Data—0
Improving Fine-Grained Control via Aggregation of Multiple Diffusion ModelsCode0
Denoising with a Joint-Embedding Predictive Architecture—0
ComfyGen: Prompt-Adaptive Workflows for Text-to-Image Generation—0
EC-DIT: Scaling Diffusion Transformers with Adaptive Expert-Choice Routing—0
DisEnvisioner: Disentangled and Enriched Visual Prompt for Customized Image Generation—0
Normalizing Flow-Based Metric for Image GenerationCode0
CusConcept: Customized Visual Concept Decomposition with Diffusion ModelsCode0
Scene Graph Disentanglement and Composition for Generalizable Complex Image Generation—0
RadGazeGen: Radiomics and Gaze-guided Medical Image Generation using Diffusion Models—0
NECOMIMI: Neural-Cognitive Multimodal EEG-informed Image Generation with Diffusion ModelsCode0
Exploring Gen-AI applications in building research and industry: A review—0
MaskMamba: A Hybrid Mamba-Transformer Model for Masked Image Generation—0
Devil is in Details: Locality-Aware 3D Abdominal CT Volume Generation for Self-Supervised Organ SegmentationCode0
Illustrious: an Open Advanced Illustration Model—0
Enhancing GANs with Contrastive Learning-Based Multistage Progressive Finetuning SNN and RL-Based External Optimization—0
CLR-GAN: Improving GANs Stability and Quality via Consistent Latent Representation and ReconstructionCode0
Inverse Painting: Reconstructing The Painting Process—0
OrganiQ: Mitigating Classical Resource Bottlenecks of Quantum Generative Adversarial Networks on NISQ-Era Machines—0
Storynizor: Consistent Story Generation via Inter-Frame Synchronized and Shuffled ID Injection—0
Introducing SDICE: An Index for Assessing Diversity of Synthetic Medical Datasets—0
FINE: Factorizing Knowledge for Initialization of Variable-sized Diffusion Models—0
Secure Multiparty Generative AI—0
Pruning then Reweighting: Towards Data-Efficient Training of Diffusion ModelsCode0
Fusion is all you need: Face Fusion for Customized Identity-Preserving Image Synthesis—0
Detecting Dataset Abuse in Fine-Tuning Stable Diffusion Models for Text-to-Image Synthesis—0
Synthesizing beta-amyloid PET images from T1-weighted Structural MRI: A Preliminary Study—0
Rejection Sampling IMLE: Designing Priors for Better Few-Shot Image Synthesis—0
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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