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 5451–5475 of 6689 papers

TitleStatusHype
LDFaceNet: Latent Diffusion-based Network for High-Fidelity Deepfake Generation—0
DiTFastAttn: Attention Compression for Diffusion Transformer Models—0
DiTFastAttnV2: Head-wise Attention Compression for Multi-Modality Diffusion Transformers—0
Ditto: Accelerating Diffusion Model via Temporal Value Similarity—0
Symmetrical Flow Matching: Unified Image Generation, Segmentation, and Classification with Score-Based Generative Models—0
DiVAE: Photorealistic Images Synthesis with Denoising Diffusion Decoder—0
Arbitrary Distributions Mapping via SyMOT-Flow: A Flow-based Approach Integrating Maximum Mean Discrepancy and Optimal Transport—0
DivCon: Divide and Conquer for Progressive Text-to-Image Generation—0
DiverGAN: An Efficient and Effective Single-Stage Framework for Diverse Text-to-Image Generation—0
Diverse and Tailored Image Generation for Zero-shot Multi-label Classification—0
Diverse Diffusion: Enhancing Image Diversity in Text-to-Image Generation—0
DiverseFlow: Sample-Efficient Diverse Mode Coverage in Flows—0
Visual Car Brand Classification by Implementing a Synthetic Image Dataset Creation Pipeline—0
SyncDiffusion: Coherent Montage via Synchronized Joint Diffusions—0
VisualCloze: A Universal Image Generation Framework via Visual In-Context Learning—0
Diverse Single Image Generation with Controllable Global Structure—0
SyncNoise: Geometrically Consistent Noise Prediction for Text-based 3D Scene Editing—0
Diversify, Don't Fine-Tune: Scaling Up Visual Recognition Training with Synthetic Images—0
Diversity and Diffusion: Observations on Synthetic Image Distributions with Stable Diffusion—0
SynNet: Structure-Preserving Fully Convolutional Networks for Medical Image Synthesis—0
Diversity Regularized Adversarial Learning—0
DIVE: Taming DINO for Subject-Driven Video Editing—0
SYNOSIS: Image synthesis pipeline for machine vision in metal surface inspection—0
Divide and Conquer: Language Models can Plan and Self-Correct for Compositional Text-to-Image Generation—0
Divide, Evaluate, and Refine: Evaluating and Improving Text-to-Image Alignment with Iterative VQA Feedback—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