Computer Vision
 
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Image Generation

1990 papers with code • 85 benchmarks • 67 datasets

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 )

Libraries

Use these libraries to find Image Generation models and implementations

Datasets

Subtasks

ANCHOR: LLM-driven News Subject Conditioning for Text-to-Image Synthesis

aashish2000/anchor • 15 Apr 2024

With Large Language Models (LLM) achieving success in language and commonsense reasoning tasks, we explore the ability of different LLMs to identify and understand key subjects from abstractive captions.

0
15 Apr 2024
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Semantic Approach to Quantifying the Consistency of Diffusion Model Image Generation

brinnaebent/semantic-consistency-score • • 12 Apr 2024

In this study, we identify the need for an interpretable, quantitative score of the repeatability, or consistency, of image generation in diffusion models.

0
12 Apr 2024
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CAT: Contrastive Adapter Training for Personalized Image Generation

faceonlive/ai-research • 11 Apr 2024

Finally, we mention the possibility of CAT in the aspects of multi-concept adapter and optimization.

161
11 Apr 2024
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Taming Stable Diffusion for Text to 360° Panorama Image Generation

faceonlive/ai-research • 11 Apr 2024

Generative models, e. g., Stable Diffusion, have enabled the creation of photorealistic images from text prompts.

161
11 Apr 2024
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Latent Guard: a Safety Framework for Text-to-image Generation

faceonlive/ai-research • 11 Apr 2024

Hence, we propose Latent Guard, a framework designed to improve safety measures in text-to-image generation.

161
11 Apr 2024
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Model-based Cleaning of the QUILT-1M Pathology Dataset for Text-Conditional Image Synthesis

deepmicroscopy/quiltcleaner • • 11 Apr 2024

The QUILT-1M dataset is the first openly available dataset containing images harvested from various online sources.

1
11 Apr 2024
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A Gauss-Newton Approach for Min-Max Optimization in Generative Adversarial Networks

faceonlive/ai-research • 10 Apr 2024

It modifies the Gauss-Newton method to approximate the min-max Hessian and uses the Sherman-Morrison inversion formula to calculate the inverse.

161
10 Apr 2024
Paper
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Deep Generative Data Assimilation in Multimodal Setting

faceonlive/ai-research • 10 Apr 2024

To our knowledge, our work is the first to apply deep generative framework for multimodal data assimilation using real-world datasets; an important step for building robust computational simulators, including the next-generation Earth system models.

161
10 Apr 2024
Paper
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StoryImager: A Unified and Efficient Framework for Coherent Story Visualization and Completion

faceonlive/ai-research • 9 Apr 2024

3) The story visualization and continuation models are trained and inferred independently, which is not user-friendly.

161
09 Apr 2024
Paper
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Hyperparameter-Free Medical Image Synthesis for Sharing Data and Improving Site-Specific Segmentation

faceonlive/ai-research • 9 Apr 2024

Sharing synthetic medical images is a promising alternative to sharing real images that can improve patient privacy and data security.

161
09 Apr 2024
Paper
Code
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