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Conditional Image Generation

Conditional image generation is the task of generating new images from a dataset conditional on their class.

( Image credit: PixelCNN++ )

Papers

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Showing 101–150 of 286 papers

TitleStatusHype
Stochastic Conditional Diffusion Models for Robust Semantic Image SynthesisCode1
Evaluating the Clinical Realism of Synthetic Chest X-Rays Generated Using Progressively Growing GANsCode1
Tell2Design: A Dataset for Language-Guided Floor Plan GenerationCode1
Text as Neural Operator: Image Manipulation by Text InstructionCode1
TinyGAN: Distilling BigGAN for Conditional Image GenerationCode1
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial NetworksCode1
VIEScore: Towards Explainable Metrics for Conditional Image Synthesis EvaluationCode1
Active Learning Inspired ControlNet Guidance for Augmenting Semantic Segmentation Datasets—0
CIMGEN: Controlled Image Manipulation by Finetuning Pretrained Generative Models on Limited Data—0
Exploring Intra-Class Variation Factors With Learnable Cluster Prompts for Semi-Supervised Image Synthesis—0
Image Generation and Translation with Disentangled Representations—0
PRISM: A Unified Framework for Photorealistic Reconstruction and Intrinsic Scene Modeling—0
Unified Multi-Modal Latent Diffusion for Joint Subject and Text Conditional Image Generation—0
Cocktail: Mixing Multi-Modality Controls for Text-Conditional Image Generation—0
ST-DDPM: Explore Class Clustering for Conditional Diffusion Probabilistic Models—0
Collage Diffusion—0
Bespoke Non-Stationary Solvers for Fast Sampling of Diffusion and Flow Models—0
Conditional Generative Data-free Knowledge Distillation—0
Adversarial Text-to-Image Synthesis: A Review—0
Conditional Image Generation with One-Vs-All Classifier—0
Self-control: A Better Conditional Mechanism for Masked Autoregressive Model—0
Conditional Image Generation with Pretrained Generative Model—0
Reconstructing the Noise Manifold for Image Denoising—0
Reconstructing the Noise Variance Manifold for Image Denoising—0
A survey on knowledge-enhanced multimodal learning—0
Condition-Aware Neural Network for Controlled Image Generation—0
Consistency Regularization for Generative Adversarial Networks—0
Constant Rate Schedule: Constant-Rate Distributional Change for Efficient Training and Sampling in Diffusion Models—0
Context-Aware Autoregressive Models for Multi-Conditional Image Generation—0
Stochastic Conditional Generative Networks with Basis Decomposition—0
Controllable Image Synthesis via SegVAE—0
Reference-based Variational Autoencoders—0
Structure-Guided Adversarial Training of Diffusion Models—0
SyncDiffusion: Coherent Montage via Synchronized Joint Diffusions—0
Ctrl-U: Robust Conditional Image Generation via Uncertainty-aware Reward Modeling—0
UNIMO-G: Unified Image Generation through Multimodal Conditional Diffusion—0
Unlocking Pre-trained Image Backbones for Semantic Image Synthesis—0
D2C: Unlocking the Potential of Continuous Autoregressive Image Generation with Discrete Tokens—0
DC-ControlNet: Decoupling Inter- and Intra-Element Conditions in Image Generation with Diffusion Models—0
Representation learning with CGAN for casual inference—0
DeepWarp: Photorealistic Image Resynthesis for Gaze Manipulation—0
In-Context Translation: Towards Unifying Image Recognition, Processing, and Generation—0
Auto-regressive Image Synthesis with Integrated Quantization—0
DiffAD: A Unified Diffusion Modeling Approach for Autonomous Driving—0
Rethinking the Objectives of Vector-Quantized Tokenizers for Image Synthesis—0
Diff-Retinex: Rethinking Low-light Image Enhancement with A Generative Diffusion Model—0
Augmented Conditioning Is Enough For Effective Training Image Generation—0
InfoCNF: An Efficient Conditional Continuous Normalizing Flow with Adaptive Solvers—0
Di[M]O: Distilling Masked Diffusion Models into One-step Generator—0
Discrete Predictor-Corrector Diffusion Models for Image Synthesis—0
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All datasetsCIFAR-10ImageNet 128x128ArtBench-10 (32x32)CIFAR-100ImageNet 64x64COCO-AnimalsImageNet 256x256CelebAMask-HQCIFAR-10 LTImageNet-LTTiny ImageNet

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Projection DiscriminatorFID17.5—Unverified
2BigGANFID14.73—Unverified
3CR-BigGANFID11.67—Unverified
4ContraGANFID10.3—Unverified
5NDAFID9.42—Unverified
6Splitting GANInception score8.87—Unverified
7WGAN-GPInception score8.67—Unverified
8SGANInception score8.59—Unverified
9AC-GANInception score8.25—Unverified
10Improved GANInception score8.09—Unverified
#ModelMetricClaimedVerifiedStatus
1AC-GANInception score28.5—Unverified
2Projection DiscriminatorFID27.62—Unverified
3SAGANFID18.65—Unverified
4Your Local GANFID15.94—Unverified
5HamGANFID14.8—Unverified
6FQ-GANFID13.77—Unverified
7BigGAN + instance selectionFID9.61—Unverified
8IC-GAN + DAFID9.5—Unverified
9Omni-GANFID8.3—Unverified
10ReACGANFID8.21—Unverified
#ModelMetricClaimedVerifiedStatus
1Projected GANFID11.84—Unverified
2BigGAN + CRFID4.65—Unverified
3StyleGAN2FID4.49—Unverified
4BigGAN + DiffAugFID4.06—Unverified
5ReACGAN + DiffAugFID3.18—Unverified
6StyleGAN2 + ADAFID2.63—Unverified
#ModelMetricClaimedVerifiedStatus
1MHingeGANFID17.3—Unverified
2aw-BigGANFID10.23—Unverified
3ADC-GANFID8.12—Unverified
4TAC-GANFID7.22—Unverified
5FQ-GANFID7.15—Unverified
6DLSMFID3.86—Unverified
#ModelMetricClaimedVerifiedStatus
1FQ-GANFID9.67—Unverified
2SAGAN + instance selectionFID9.07—Unverified
3IC-GAN + DAFID6.7—Unverified
#ModelMetricClaimedVerifiedStatus
1BigGANFID16.37—Unverified
2U-Net GANFID13.73—Unverified
#ModelMetricClaimedVerifiedStatus
1BigGAN+ [Brock et al.] (chx96)FID8.1—Unverified
2DiGITFID3.39—Unverified
#ModelMetricClaimedVerifiedStatus
1SCDMFID17.4—Unverified
#ModelMetricClaimedVerifiedStatus
1BigGAN + gSRFID12.03—Unverified
#ModelMetricClaimedVerifiedStatus
1StyleGAN2 + NoisyTwinsFID21.29—Unverified
#ModelMetricClaimedVerifiedStatus
1ADC-GANFID19.02—Unverified