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 16261650 of 6689 papers

TitleStatusHype
EDT: An Efficient Diffusion Transformer Framework Inspired by Human-like SketchingCode1
Continuous Speculative Decoding for Autoregressive Image GenerationCode1
Efficient Content-Based Sparse Attention with Routing TransformersCode1
Continuous Language Generative FlowCode1
3D-Aware Semantic-Guided Generative Model for Human SynthesisCode1
Editing in Style: Uncovering the Local Semantics of GANsCode1
Elucidating The Design Space of Classifier-Guided Diffusion GenerationCode1
DiffuGen: Adaptable Approach for Generating Labeled Image Datasets using Stable Diffusion ModelsCode1
BS-Diff: Effective Bone Suppression Using Conditional Diffusion Models from Chest X-Ray ImagesCode1
BS-LDM: Effective Bone Suppression in High-Resolution Chest X-Ray Images with Conditional Latent Diffusion ModelsCode1
Diffuse Everything: Multimodal Diffusion Models on Arbitrary State SpacesCode1
DiffuseExpand: Expanding dataset for 2D medical image segmentation using diffusion modelsCode1
Unsupervised Sketch-to-Photo SynthesisCode1
Manipulating Embeddings of Stable Diffusion PromptsCode1
MedITok: A Unified Tokenizer for Medical Image Synthesis and InterpretationCode1
Synthesizing Optical and SAR Imagery From Land Cover Maps and Auxiliary Raster DataCode1
Modulated Contrast for Versatile Image SynthesisCode1
Continual Learning of Diffusion Models with Generative DistillationCode1
ConTEXTual Net: A Multimodal Vision-Language Model for Segmentation of PneumothoraxCode1
Attribute-guided image generation from layoutCode1
Contextual Convolutional Neural NetworksCode1
Attribute Group Editing for Reliable Few-shot Image GenerationCode1
Anycost GANs for Interactive Image Synthesis and EditingCode1
C2N: Practical Generative Noise Modeling for Real-World DenoisingCode1
Echo from noise: synthetic ultrasound image generation using diffusion models for real image segmentationCode1
Show:102550
← PrevPage 66 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