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Unconditional Image Generation

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Showing 26–50 of 73 papers

TitleStatusHype
Dual Contrastive Loss and Attention for GANsCode1
Negative Data AugmentationCode1
Adaptive Weighted Discriminator for Training Generative Adversarial NetworksCode1
Learning Semantic-aware Normalization for Generative Adversarial NetworksCode1
Hijack-GAN: Unintended-Use of Pretrained, Black-Box GANsCode1
Score-Based Generative Modeling through Stochastic Differential EquationsCode1
Large Scale Adversarial Representation LearningCode1
DiffUMI: Training-Free Universal Model Inversion via Unconditional Diffusion for Face Recognition—0
Acquire and then Adapt: Squeezing out Text-to-Image Model for Image Restoration—0
Entropy Rectifying Guidance for Diffusion and Flow Models—0
A Unified Framework for Diffusion Bridge Problems: Flow Matching and Schrödinger Matching into One—0
Conjuring Positive Pairs for Efficient Unification of Representation Learning and Image Synthesis—0
Training-Free Safe Denoisers for Safe Use of Diffusion Models—0
PQD: Post-training Quantization for Efficient Diffusion Models—0
Enhancing Low Dose Computed Tomography Images Using Consistency Training Techniques—0
Scalable, Tokenization-Free Diffusion Model Architectures with Efficient Initial Convolution and Fixed-Size Reusable Structures for On-Device Image Generation—0
Variational Potential Flow: A Novel Probabilistic Framework for Energy-Based Generative Modelling—0
Deep MMD Gradient Flow without adversarial training—0
Generative Modelling with High-Order Langevin Dynamics—0
LD-Pruner: Efficient Pruning of Latent Diffusion Models using Task-Agnostic Insights—0
Diffscaler: Enhancing the Generative Prowess of Diffusion Transformers—0
Iso-Diffusion: Improving Diffusion Probabilistic Models Using the Isotropy of the Additive Gaussian Noise—0
Improving Diffusion-Based Image Synthesis with Context Prediction—0
Wasserstein Convergence Guarantees for a General Class of Score-Based Generative Models—0
DIFFNAT: Improving Diffusion Image Quality Using Natural Image Statistics—0
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