Segmentation and depth-maps are required to use new images as background. Sample scripts for obtaining these are available here. predict_depth.m MATLAB script to regress a depth mask …

With efficient texture adaptation fine-tuning, TexDreamer exhibits faithful identity and clothing for generating semantic 3D human UV textures from texts. Additionally, leveraging a novel feature …

Jul 20, 2021 · Specifically, they generate multiple text images with diverse backgrounds, font styles, and text shapes and enable STR models to learn visual patterns that might not be …

Aug 19, 2023 · We propose a conditional GAN, Text and Background Mapping GAN (TBM-GAN), to synthesise handwritten images with noisy background texture. Given a text image on clean …

Specifically, they generate multiple text images with diverse backgrounds, font styles, and text shapes and enable STR models to learn visual patterns that might not be accessible from …

Text2Tex generates high-quality textures for 3D meshes from the given text prompts. Our method incorporates inpainting into a pre-trained depth-aware image diffusion model to progressively …

Nov 15, 2024 · To reduce this engineering effort, we investigate the use of pretrained text-to-image diffusion models for texturing synthetic images and compare this approach with using …

We present , the first zero-shot multimodal high-fidelity 3D human texture generation model. Utilizing an eficient texture adaptation finetuning strategy, we adapt large T2I model to a …

Specifically, they generate multiple text images with diverse backgrounds, font styles, and text shapes and enable STR models to learn visual patterns that might not be accessible from …

First, we propose a new method for gen-erating synthetic images of text that naturally blends text in existing natural scenes, using off-the-shelf deep learning and segmentation techniques to …