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Found 6 papers, 0 papers with code
Refining Text-to-Image Generation: Towards Accurate Training-Free Glyph-Enhanced Image Generation
We introduce a benchmark, LenCom-Eval, specifically designed for testing models' capability in generating images with Lengthy and Complex visual text.
Optical Character Recognition (OCR)
Text-to-Image Generation
Source-Free Domain Adaptation with Diffusion-Guided Source Data Generation
Our proposed DM-SFDA method involves fine-tuning a pre-trained text-to-image diffusion model to generate source domain images using features from the target images to guide the diffusion process.
Source-Free Domain Adaptation
Unsupervised Domain Adaptation
Learning to Discern: Imitating Heterogeneous Human Demonstrations with Preference and Representation Learning
Furthermore, the intrinsic heterogeneity in human behavior can produce equally successful but disparate demonstrations, further exacerbating the challenge of discerning demonstration quality.
Transcending Domains through Text-to-Image Diffusion: A Source-Free Approach to Domain Adaptation
Domain Adaptation (DA) is a method for enhancing a model's performance on a target domain with inadequate annotated data by applying the information the model has acquired from a related source domain with sufficient labeled data.
Active Data Discovery: Mining Unknown Data using Submodular Information Measures
Most approaches assume access to a seed set of instances which contain these rare data instances.
Open Domain Suggestion Mining Leveraging Fine-Grained Analysis
Finally, we discuss the practical, computational and reproducibility aspects of the deployment of our pipeline across the web.
