StyleText is a new large-scale dataset and benchmark for stylized scene text inpainting, constructed via an automated pipeline and paired with a FluxFill+LoRA baseline that improves OCR accuracy.
Adding conditional control to text-to-image diffusion models
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
fields
cs.CV 2verdicts
UNVERDICTED 2representative citing papers
A feed-forward video latent transformer that predicts time-varying 3D Gaussian primitives from one image to produce controllable 4D scenes with appearance, geometry, and motion.
citing papers explorer
-
StyleText: A Large-Scale Dataset and Benchmark for Stylized Scene Text Inpainting
StyleText is a new large-scale dataset and benchmark for stylized scene text inpainting, constructed via an automated pipeline and paired with a FluxFill+LoRA baseline that improves OCR accuracy.
-
Diff4Splat: Controllable 4D Scene Generation with Latent Dynamic Reconstruction Models
A feed-forward video latent transformer that predicts time-varying 3D Gaussian primitives from one image to produce controllable 4D scenes with appearance, geometry, and motion.