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 4851–4900 of 6689 papers

TitleStatusHype
A Diffusion-based Method for Multi-turn Compositional Image Generation—0
Taming Encoder for Zero Fine-tuning Image Customization with Text-to-Image Diffusion Models—0
Toward Verifiable and Reproducible Human Evaluation for Text-to-Image Generation—0
Cross-modal tumor segmentation using generative blending augmentation and self trainingCode0
Text-Conditioned Sampling Framework for Text-to-Image Generation with Masked Generative Models—0
MetaHead: An Engine to Create Realistic Digital Head—0
CG-3DSRGAN: A classification guided 3D generative adversarial network for image quality recovery from low-dose PET images—0
ViT-DAE: Transformer-driven Diffusion Autoencoder for Histopathology Image Analysis—0
Textile Pattern Generation Using Diffusion Models—0
Learning Dynamic Style Kernels for Artistic Style Transfer—0
PrefGen: Preference Guided Image Generation with Relative AttributesCode0
Subject-driven Text-to-Image Generation via Apprenticeship Learning—0
Trade-offs in Fine-tuned Diffusion Models Between Accuracy and InterpretabilityCode0
3D-aware Image Generation using 2D Diffusion Models—0
GVP: Generative Volumetric Primitives—0
Social Biases through the Text-to-Image Generation Lens—0
Semantic Image Translation for Repairing the Texture Defects of Building Models—0
KD-DLGAN: Data Limited Image Generation via Knowledge Distillation—0
DiffCollage: Parallel Generation of Large Content with Diffusion Models—0
SC-VAE: Sparse Coding-based Variational Autoencoder with Learned ISTACode0
Qualitative Failures of Image Generation Models and Their Application in Detecting Deepfakes—0
Instant Photorealistic Neural Radiance Fields StylizationCode0
DDMM-Synth: A Denoising Diffusion Model for Cross-modal Medical Image Synthesis with Sparse-view Measurement Embedding—0
Variational Distribution Learning for Unsupervised Text-to-Image Generation—0
Mask and Restore: Blind Backdoor Defense at Test Time with Masked AutoencoderCode0
Object-Centric Relational Representations for Image GenerationCode0
Learning Versatile 3D Shape Generation with Improved AR Models—0
Joint fMRI Decoding and Encoding with Latent Embedding Alignment—0
Learning Generative Models with Goal-conditioned Reinforcement Learning—0
BlobGAN-3D: A Spatially-Disentangled 3D-Aware Generative Model for Indoor Scenes—0
Spatial Latent Representations in Generative Adversarial Networks for Image Generation—0
Causal Image Synthesis of Brain MR in 3D—0
Indonesian Text-to-Image Synthesis with Sentence-BERT and FastGANCode0
Factor Decomposed Generative Adversarial Networks for Text-to-Image Synthesis—0
MagicFusion: Boosting Text-to-Image Generation Performance by Fusing Diffusion Models—0
Explore the Power of Synthetic Data on Few-shot Object Detection—0
CoBIT: A Contrastive Bi-directional Image-Text Generation Model—0
VecFontSDF: Learning to Reconstruct and Synthesize High-quality Vector Fonts via Signed Distance FunctionsCode0
Affordance Diffusion: Synthesizing Hand-Object Interactions—0
CoopInit: Initializing Generative Adversarial Networks via Cooperative Learning—0
DiffuMask: Synthesizing Images with Pixel-level Annotations for Semantic Segmentation Using Diffusion ModelsCode0
Picture that Sketch: Photorealistic Image Generation from Abstract Sketches—0
NASDM: Nuclei-Aware Semantic Histopathology Image Generation Using Diffusion Models—0
Less is More: Unsupervised Mask-guided Annotated CT Image Synthesis with Minimum Manual Segmentations—0
MRIS: A Multi-modal Retrieval Approach for Image Synthesis on Diverse Modalities—0
Unsupervised Domain Transfer with Conditional Invertible Neural Networks—0
Unified Multi-Modal Latent Diffusion for Joint Subject and Text Conditional Image Generation—0
Conditional Synthetic Food Image Generation—0
Mimic3D: Thriving 3D-Aware GANs via 3D-to-2D Imitation—0
Class Attribute Inference Attacks: Inferring Sensitive Class Information by Diffusion-Based Attribute ManipulationsCode0
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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