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 2751–2800 of 6689 papers

TitleStatusHype
Anatomically-Controllable Medical Image Generation with Segmentation-Guided Diffusion ModelsCode3
ColorSwap: A Color and Word Order Dataset for Multimodal EvaluationCode1
ChatScratch: An AI-Augmented System Toward Autonomous Visual Programming Learning for Children Aged 6-12—0
Noise Map Guidance: Inversion with Spatial Context for Real Image EditingCode1
Text2Street: Controllable Text-to-image Generation for Street Views—0
Breaking Free: How to Hack Safety Guardrails in Black-Box Diffusion Models!Code0
QuEST: Low-bit Diffusion Model Quantization via Efficient Selective FinetuningCode2
FoolSDEdit: Deceptively Steering Your Edits Towards Targeted Attribute-aware Distribution—0
IGUANe: a 3D generalizable CycleGAN for multicenter harmonization of brain MR imagesCode1
Do Diffusion Models Learn Semantically Meaningful and Efficient Representations?—0
InstanceDiffusion: Instance-level Control for Image GenerationCode4
Training-Free Consistent Text-to-Image GenerationCode2
M^3Face: A Unified Multi-Modal Multilingual Framework for Human Face Generation and Editing—0
DiffEditor: Boosting Accuracy and Flexibility on Diffusion-based Image EditingCode4
Separable Multi-Concept Erasure from Diffusion Models—0
Diffusion Cross-domain RecommendationCode1
Risk-Sensitive Diffusion: Robustly Optimizing Diffusion Models with Noisy Samples—0
Mobile Fitting Room: On-device Virtual Try-on via Diffusion Models—0
Variational Quantum Circuits Enhanced Generative Adversarial Network—0
Neural Language of Thought Models—0
On the Multi-modal Vulnerability of Diffusion ModelsCode1
Can Shape-Infused Joint Embeddings Improve Image-Conditioned 3D Diffusion?—0
Can MLLMs Perform Text-to-Image In-Context Learning?Code1
Cross-view Masked Diffusion Transformers for Person Image SynthesisCode2
Unconditional Latent Diffusion Models Memorize Patient Imaging Data: Implications for Openly Sharing Synthetic DataCode0
CapHuman: Capture Your Moments in Parallel UniversesCode2
AnimateLCM: Computation-Efficient Personalized Style Video Generation without Personalized Video DataCode4
High-Quality Medical Image Generation from Free-hand Sketch—0
Diffusion Model Compression for Image-to-Image Translation—0
Head and Neck Tumor Segmentation from [18F]F-FDG PET/CT Images Based on 3D Diffusion Model—0
Fréchet Distance for Offline Evaluation of Information Retrieval Systems with Sparse Labels—0
Image Anything: Towards Reasoning-coherent and Training-free Multi-modal Image Generation—0
Beyond Inserting: Learning Identity Embedding for Semantic-Fidelity Personalized Diffusion Generation—0
Through-Wall Imaging based on WiFi Channel State InformationCode1
Repositioning the Subject within ImageCode1
X-ray Image Generation as a Method of Performance Prediction for Real-Time Inspection: a Case StudyCode0
Multilingual Text-to-Image Generation Magnifies Gender Stereotypes and Prompt Engineering May Not Help YouCode0
Bridging Generative and Discriminative Models for Unified Visual Perception with Diffusion Priors—0
Diffutoon: High-Resolution Editable Toon Shading via Diffusion Models—0
Diffusion Facial Forgery DetectionCode2
Spatial-Aware Latent Initialization for Controllable Image Generation—0
Divide and Conquer: Language Models can Plan and Self-Correct for Compositional Text-to-Image Generation—0
Object-Driven One-Shot Fine-tuning of Text-to-Image Diffusion with Prototypical Embedding—0
GEM: Boost Simple Network for Glass Surface Segmentation via Segment Anything Model and Data SynthesisCode1
Taiyi-Diffusion-XL: Advancing Bilingual Text-to-Image Generation with Large Vision-Language Model SupportCode1
Annotated Hands for Generative ModelsCode0
Diffusion Enhancement for Cloud Removal in Ultra-Resolution Remote Sensing ImageryCode2
BootPIG: Bootstrapping Zero-shot Personalized Image Generation Capabilities in Pretrained Diffusion ModelsCode1
Deconstructing Denoising Diffusion Models for Self-Supervised LearningCode2
UrbanGenAI: Reconstructing Urban Landscapes using Panoptic Segmentation and Diffusion Models—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