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 5151–5200 of 6689 papers

TitleStatusHype
Programmable-Room: Interactive Textured 3D Room Meshes Generation Empowered by Large Language Models—0
WorldGenBench: A World-Knowledge-Integrated Benchmark for Reasoning-Driven Text-to-Image Generation—0
Progressive Compression with Universally Quantized Diffusion Models—0
Unlimited Resolution Image Generation with R2D2-GANs—0
Progressive Text-to-Image Generation—0
Progressive distillation diffusion for raw music generation—0
Altogether: Image Captioning via Re-aligning Alt-text—0
Alteration-free and Model-agnostic Origin Attribution of Generated Images—0
Progressively Growing Generative Adversarial Networks for High Resolution Semantic Segmentation of Satellite Images—0
Progressively Unfreezing Perceptual GAN—0
2D GANs Meet Unsupervised Single-view 3D Reconstruction—0
Progressive Retinex: Mutually Reinforced Illumination-Noise Perception Network for Low Light Image Enhancement—0
Unlocking Aha Moments via Reinforcement Learning: Advancing Collaborative Visual Comprehension and Generation—0
Progress Towards Decoding Visual Imagery via fNIRS—0
Rethinking Training for De-biasing Text-to-Image Generation: Unlocking the Potential of Stable Diffusion—0
Projection image-to-image translation in hybrid X-ray/MR imaging—0
Prometheus: 3D-Aware Latent Diffusion Models for Feed-Forward Text-to-3D Scene Generation—0
Unlocking Pre-trained Image Backbones for Semantic Image Synthesis—0
Prompt Augmentation for Self-supervised Text-guided Image Manipulation—0
Unlocking Spatial Comprehension in Text-to-Image Diffusion Models—0
PromptCrafter: Crafting Text-to-Image Prompt through Mixed-Initiative Dialogue with LLM—0
ForgetMe: Evaluating Selective Forgetting in Generative Models—0
A Taxonomy of Prompt Modifiers for Text-To-Image Generation—0
Prompt Expansion for Adaptive Text-to-Image Generation—0
ALR-GAN: Adaptive Layout Refinement for Text-to-Image Synthesis—0
A LoRA is Worth a Thousand Pictures—0
PromptGuard: Soft Prompt-Guided Unsafe Content Moderation for Text-to-Image Models—0
Promptify: Text-to-Image Generation through Interactive Prompt Exploration with Large Language Models—0
Prompting Forgetting: Unlearning in GANs via Textual Guidance—0
Prompting Hard or Hardly Prompting: Prompt Inversion for Text-to-Image Diffusion Models—0
Prompt Mechanisms in Medical Imaging: A Comprehensive Survey—0
PromptMobile: Efficient Promptus for Low Bandwidth Mobile Video Streaming—0
Prompt Performance Prediction for Image Generation—0
Prompt-Propose-Verify: A Reliable Hand-Object-Interaction Data Generation Framework using Foundational Models—0
Prompt Recovery for Image Generation Models: A Comparative Study of Discrete Optimizers—0
World Knowledge from AI Image Generation for Robot Control—0
Unlocking Visual Secrets: Inverting Features with Diffusion Priors for Image Reconstruction—0
Prompt-Softbox-Prompt: A free-text Embedding Control for Image Editing—0
Unmasking the Canvas: A Dynamic Benchmark for Image Generation Jailbreaking and LLM Content Safety—0
All but One: Surgical Concept Erasing with Model Preservation in Text-to-Image Diffusion Models—0
Prompt Tuning Inversion for Text-Driven Image Editing Using Diffusion Models—0
Unmixing Before Fusion: A Generalized Paradigm for Multi-Source-based Hyperspectral Image Synthesis—0
ProstateGAN: Mitigating Data Bias via Prostate Diffusion Imaging Synthesis with Generative Adversarial Networks—0
Unpaired Brain MR-to-CT Synthesis using a Structure-Constrained CycleGAN—0
Protecting Intellectual Property of Generative Adversarial Networks From Ambiguity Attacks—0
Protective Perturbations against Unauthorized Data Usage in Diffusion-based Image Generation—0
Prototype memory and attention mechanisms for few shot image generation—0
Provably Secure Robust Image Steganography via Cross-Modal Error Correction—0
Proxy-Tuning: Tailoring Multimodal Autoregressive Models for Subject-Driven Image Generation—0
Align Your Flow: Scaling Continuous-Time Flow Map Distillation—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