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 5751–5800 of 6689 papers

TitleStatusHype
Example-Guided Image Synthesis using Masked Spatial-Channel Attention and Self-Supervision—0
Example-Guided Scene Image Synthesis using Masked Spatial-Channel Attention and Patch-Based Self-Supervision—0
Example-Guided Style-Consistent Image Synthesis From Semantic Labeling—0
TCFG: Tangential Damping Classifier-free Guidance—0
Exemplar-based Generative Facial Editing—0
Exocentric to Egocentric Image Generation via Parallel Generative Adversarial Network—0
Experiments on Generative AI-Powered Parametric Modeling and BIM for Architectural Design—0
Explainable Concept Generation through Vision-Language Preference Learning—0
TcGAN: Semantic-Aware and Structure-Preserved GANs with Individual Vision Transformer for Fast Arbitrary One-Shot Image Generation—0
TCIG: Two-Stage Controlled Image Generation with Quality Enhancement through Diffusion—0
Explicit Gradient Learning—0
Explicit Gradient Learning for Black-Box Optimization—0
BitsFusion: 1.99 bits Weight Quantization of Diffusion Model—0
Exploiting Knowledge Distillation for Few-Shot Image Generation—0
Exploiting Relationship for Complex-scene Image Generation—0
Exploiting Watermark-Based Defense Mechanisms in Text-to-Image Diffusion Models for Unauthorized Data Usage—0
Explore the Power of Synthetic Data on Few-shot Object Detection—0
Explore the vulnerability of black-box models via diffusion models—0
Exploring Cellular Protein Localization Through Semantic Image Synthesis—0
Exploring Compositional Visual Generation with Latent Classifier Guidance—0
Visual Relationship Detection using Scene Graphs: A Survey—0
TDRI: Two-Phase Dialogue Refinement and Co-Adaptation for Interactive Image Generation—0
Exploring Disentangled and Controllable Human Image Synthesis: From End-to-End to Stage-by-Stage—0
VisualSphinx: Large-Scale Synthetic Vision Logic Puzzles for RL—0
Teaching Metric Distance to Autoregressive Multimodal Foundational Models—0
Exploring Intra-Class Variation Factors With Learnable Cluster Prompts for Semi-Supervised Image Synthesis—0
Exploring Language Patterns of Prompts in Text-to-Image Generation and Their Impact on Visual Diversity—0
Teaching Text-to-Image Models to Communicate in Dialog—0
Exploring Position Encoding in Diffusion U-Net for Training-free High-resolution Image Generation—0
Exploring Social Bias in Downstream Applications of Text-to-Image Foundation Models—0
Exploring StyleGAN Latent Space for Face Alignment with Limited Training Data—0
BitMark for Infinity: Watermarking Bitwise Autoregressive Image Generative Models—0
Exploring the Effectiveness of Deep Features from Domain-Specific Foundation Models in Retinal Image Synthesis—0
Exploring the Effectiveness of Mask-Guided Feature Modulation as a Mechanism for Localized Style Editing of Real Images—0
Exploring the Potential of Generative AI for the World Wide Web—0
Exploring the Role of Large Language Models in Prompt Encoding for Diffusion Models—0
Exploring Transformer Backbones for Image Diffusion Models—0
Exploring Variational Autoencoders for Medical Image Generation: A Comprehensive Study—0
Exploring Visual Vulnerabilities via Multi-Loss Adversarial Search for Jailbreaking Vision-Language Models—0
Bi-parametric prostate MR image synthesis using pathology and sequence-conditioned stable diffusion—0
Exposing GAN-synthesized Faces Using Landmark Locations—0
Exposing the Fake: Effective Diffusion-Generated Images Detection—0
Bracket Diffusion: HDR Image Generation by Consistent LDR Denoising—0
BiomedJourney: Counterfactual Biomedical Image Generation by Instruction-Learning from Multimodal Patient Journeys—0
ExSinGAN: Learning an Explainable Generative Model from a Single Image—0
TEDi: Temporally-Entangled Diffusion for Long-Term Motion Synthesis—0
SkyDiffusion: Ground-to-Aerial Image Synthesis with Diffusion Models and BEV Paradigm—0
Extracting Semantic Knowledge from GANs with Unsupervised Learning—0
Extrapolating Prospective Glaucoma Fundus Images through Diffusion Model in Irregular Longitudinal Sequences—0
ExtremeAIGC: Benchmarking LMM Vulnerability to AI-Generated Extremist Content—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