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

Showing 56265650 of 6689 papers

TitleStatusHype
Improving Text to Image Generation using Mode-seeking Function0
Category Level Object Pose Estimation via Neural Analysis-by-Synthesis0
Person image generation with semantic attention network for person re-identification0
Learning Flow-based Feature Warping for Face Frontalization with Illumination Inconsistent SupervisionCode1
Audio Dequantization for High Fidelity Audio Generation in Flow-based Neural Vocoder0
DF-GAN: A Simple and Effective Baseline for Text-to-Image SynthesisCode1
Uncertainty Quantification using Variational Inference for Biomedical Image SegmentationCode0
Text as Neural Operator: Image Manipulation by Text InstructionCode1
Implanting Synthetic Lesions for Improving Liver Lesion Segmentation in CT Exams0
Bipartite Graph Reasoning GANs for Person Image GenerationCode1
Road Segmentation for Remote Sensing Images using Adversarial Spatial Pyramid NetworksCode1
Deep Sketch-guided Cartoon Video InbetweeningCode1
Forget About the LiDAR: Self-Supervised Depth Estimators with MED Probability VolumesCode1
Block Shuffle: A Method for High-resolution Fast Style Transfer with Limited MemoryCode1
Multimodal Image-to-Image Translation via Mutual Information Estimation and Maximization0
Fighting Deepfake by Exposing the Convolutional Traces on Images0
Improving the Speed and Quality of GAN by Adversarial TrainingCode1
Image Generation for Efficient Neural Network Training in Autonomous Drone RacingCode1
Gibbs Sampling with People0
GL-GAN: Adaptive Global and Local Bilevel Optimization model of Image Generation0
Axiom-based Grad-CAM: Towards Accurate Visualization and Explanation of CNNsCode1
Hierarchical Amortized Training for Memory-efficient High Resolution 3D GANCode1
F2GAN: Fusing-and-Filling GAN for Few-shot Image GenerationCode1
Rethinking Image Deraining via Rain Streaks and VaporsCode1
Deep Novel View Synthesis from Colored 3D Point CloudsCode1
Show:102550
← PrevPage 226 of 268Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Improved DDPMFID12.3Unverified
2ADMFID11.84Unverified
3BigGAN-deepFID8.1Unverified
4Polarity-BigGANFID6.82Unverified
5VQGAN+Transformer (k=mixed, p=1.0, a=0.005)FID6.59Unverified
6MaskGITFID6.18Unverified
7VQGAN+Transformer (k=600, p=1.0, a=0.05)FID5.2Unverified
8CDMFID4.88Unverified
9ADM-GFID4.59Unverified
10RINFID4.51Unverified
#ModelMetricClaimedVerifiedStatus
1PresGANFID52.2Unverified
2RESFLOWFID48.29Unverified
3Residual FlowFID46.37Unverified
4GLF+perceptual loss (ours)FID44.6Unverified
5ProdPoly no activation functionsFID40.45Unverified
6ProdPoly no activation functionsFID36.77Unverified
7ACGANFID35.47Unverified
8DenseFlow-74-10FID34.9Unverified
9NVAE w/ flowFID32.53Unverified
10QSNGANFID31.97Unverified
#ModelMetricClaimedVerifiedStatus
1GLIDE + CLSFID30.87Unverified
2GLIDE + CLIPFID30.46Unverified
3GLIDE + CLS-FREEFID29.22Unverified
4GLIDE + CLIP + CLS + CLS-FREEFID29.18Unverified
5PGMGANFID21.73Unverified
6CLR-GANFID20.27Unverified
7FMFID14.45Unverified
8CT (Direct Generation, NFE=1)FID13Unverified
9CT (Direct Generation, NFE=2)FID11.1Unverified
10GLIDE +CLSKID7.95Unverified