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 6201–6250 of 6689 papers

TitleStatusHype
The Brittleness of AI-Generated Image Watermarking Techniques: Examining Their Robustness Against Visual Paraphrasing Attacks—0
GenFlow: Interactive Modular System for Image Generation—0
GENHOP: An Image Generation Method Based on Successive Subspace Learning—0
The Challenges of Image Generation Models in Generating Multi-Component Images—0
AC-LoRA: Auto Component LoRA for Personalized Artistic Style Image Generation—0
GenLit: Reformulating Single-Image Relighting as Video Generation—0
A Wavelet Diffusion GAN for Image Super-Resolution—0
GenSpace: Benchmarking Spatially-Aware Image Generation—0
A Watermark for Auto-Regressive Image Generation Models—0
GeoBiked: A Dataset with Geometric Features and Automated Labeling Techniques to Enable Deep Generative Models in Engineering Design—0
Active Image Synthesis for Efficient Labeling—0
Geometrically Matched Multi-source Microscopic Image Synthesis Using Bidirectional Adversarial Networks—0
Geometric Generative Models based on Morphological Equivariant PDEs and GANs—0
Geometric Image Synthesis—0
Geometric Median Matching for Robust k-Subset Selection from Noisy Data—0
Geometric Regularity in Deterministic Sampling of Diffusion-based Generative Models—0
Geometry-Aware Satellite-to-Ground Image Synthesis for Urban Areas—0
A Visual Tour Of Current Challenges In Multimodal Language Models—0
Geometry-guided Cross-view Diffusion for One-to-many Cross-view Image Synthesis—0
The CLIP Model is Secretly an Image-to-Prompt Converter—0
A Vision Check-up for Language Models—0
The Crystal Ball Hypothesis in diffusion models: Anticipating object positions from initial noise—0
GETAvatar: Generative Textured Meshes for Animatable Human Avatars—0
GH-Feat: Learning Versatile Generative Hierarchical Features from GANs—0
Gibbs Sampling with People—0
The Cultivated Practices of Text-to-Image Generation—0
A Vessel-Segmentation-Based CycleGAN for Unpaired Multi-modal Retinal Image Synthesis—0
VM-DDPM: Vision Mamba Diffusion for Medical Image Synthesis—0
GIST: Towards Photorealistic Style Transfer via Multiscale Geometric Representations—0
GIU-GANs: Global Information Utilization for Generative Adversarial Networks—0
The Effectiveness of Temporal Dependency in Deepfake Video Detection—0
The Effect of Training Dataset Size on Discriminative and Diffusion-Based Speech Enhancement Systems—0
GLASS: Guided Latent Slot Diffusion for Object-Centric Learning—0
Glauber Generative Model: Discrete Diffusion Models via Binary Classification—0
Temporal Evolution of Knee Osteoarthritis: A Diffusion-based Morphing Model for X-ray Medical Image Synthesis—0
GL-GAN: Adaptive Global and Local Bilevel Optimization model of Image Generation—0
Autoregressive Score Matching—0
Semantically Consistent Person Image Generation—0
Global Context with Discrete Diffusion in Vector Quantised Modelling for Image Generation—0
Global-Local Image Perceptual Score (GLIPS): Evaluating Photorealistic Quality of AI-Generated Images—0
GLocal: Global Graph Reasoning and Local Structure Transfer for Person Image Generation—0
GLoD: Composing Global Contexts and Local Details in Image Generation—0
The Entoptic Field Camera as Metaphor-Driven Research-through-Design with AI Technologies—0
The ethical situation of DALL-E 2—0
Glyph-ByT5: A Customized Text Encoder for Accurate Visual Text Rendering—0
GMM-Based Generative Adversarial Encoder Learning—0
Going the Extra Mile in Face Image Quality Assessment: A Novel Database and Model—0
Auto-regressive Image Synthesis with Integrated Quantization—0
Good Seed Makes a Good Crop: Discovering Secret Seeds in Text-to-Image Diffusion Models—0
Autoregressive Image Generation Guided by Chains of Thought—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