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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 6251–6300 of 6689 papers

TitleStatusHype
VODiff: Controlling Object Visibility Order in Text-to-Image Generation—0
GPS as a Control Signal for Image Generation—0
GPT4Motion: Scripting Physical Motions in Text-to-Video Generation via Blender-Oriented GPT Planning—0
Autonomy 2.0: Why is self-driving always 5 years away?—0
A robust and scalable framework for hallucination detection in virtual tissue staining and digital pathology—0
GPT-4V(ision) as a Generalist Evaluator for Vision-Language Tasks—0
GPTDrawer: Enhancing Visual Synthesis through ChatGPT—0
Gradient Domain Diffusion Models for Image Synthesis—0
Gradient-Free Classifier Guidance for Diffusion Model Sampling—0
Gradient-Free Textual Inversion—0
Gradient-Guided Conditional Diffusion Models for Private Image Reconstruction: Analyzing Adversarial Impacts of Differential Privacy and Denoising—0
Gradient-Informed Quality Diversity for the Illumination of Discrete Spaces—0
The Fabrication of Reality and Fantasy: Scene Generation with LLM-Assisted Prompt Interpretation—0
Gradpaint: Gradient-Guided Inpainting with Diffusion Models—0
GRAM: Generative Radiance Manifolds for 3D-Aware Image Generation—0
GRAM-HD: 3D-Consistent Image Generation at High Resolution with Generative Radiance Manifolds—0
GraN-GAN: Piecewise Gradient Normalization for Generative Adversarial Networks—0
GraPE: A Generate-Plan-Edit Framework for Compositional T2I Synthesis—0
Graph Flow Matching: Enhancing Image Generation with Neighbor-Aware Flow Fields—0
GRAPHGPT-O: Synergistic Multimodal Comprehension and Generation on Graphs—0
ACE++: Instruction-Based Image Creation and Editing via Context-Aware Content Filling—0
GraspDiffusion: Synthesizing Realistic Whole-body Hand-Object Interaction—0
Grassmannian Geometry Meets Dynamic Mode Decomposition in DMD-GEN: A New Metric for Mode Collapse in Time Series Generative Models—0
Medical Image Super-Resolution Using a Generative Adversarial Network—0
Grid Diffusion Models for Text-to-Video Generation—0
GridFace: Face Rectification via Learning Local Homography Transformations—0
The Hidden Cost of an Image: Quantifying the Energy Consumption of AI Image Generation—0
Grimm in Wonderland: Prompt Engineering with Midjourney to Illustrate Fairytales—0
GRIN: Zero-Shot Metric Depth with Pixel-Level Diffusion—0
Automatic Ischemic Stroke Lesion Segmentation from Computed Tomography Perfusion Images by Image Synthesis and Attention-Based Deep Neural Networks—0
Grounded Answers for Multi-agent Decision-making Problem through Generative World Model—0
Grounded Compositional and Diverse Text-to-3D with Pretrained Multi-View Diffusion Model—0
Grounded Text-to-Image Synthesis with Attention Refocusing—0
GroundingBooth: Grounding Text-to-Image Customization—0
Grounding Text-To-Image Diffusion Models For Controlled High-Quality Image Generation—0
Automatic Correction of Internal Units in Generative Neural Networks—0
Guardians of Generation: Dynamic Inference-Time Copyright Shielding with Adaptive Guidance for AI Image Generation—0
Automatic Controllable Colorization via Imagination—0
Guide3D: Create 3D Avatars from Text and Image Guidance—0
Guided Co-Modulated GAN for 360° Field of View Extrapolation—0
Guided Conditional Diffusion Classifier (ConDiff) for Enhanced Prediction of Infection in Diabetic Foot Ulcers—0
Guided Flows for Generative Modeling and Decision Making—0
Guided Frequency Loss for Image Restoration—0
The Hyperfitting Phenomenon: Sharpening and Stabilizing LLMs for Open-Ended Text Generation—0
Guided Latent Slot Diffusion for Object-Centric Learning—0
GuidedStyle: Attribute Knowledge Guided Style Manipulation for Semantic Face Editing—0
Guide Me: Interacting with Deep Networks—0
Automated Classification of Nanoparticles with Various Ultrastructures and Sizes—0
Guiding Diffusion with Deep Geometric Moments: Balancing Fidelity and Variation—0
Guiding GANs: How to control non-conditional pre-trained GANs for conditional image generation—0
Show:102550
← PrevPage 126 of 134Next →
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