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GLIDE is a generative model designed for text-to-image synthesis, image editing, and the contextual filling of masked image regions. It uses a guided diffusion process to transform random noise into high-resolution imagery that aligns with descriptive text prompts. The system provides specialized capabilities for modifying existing visuals, including the ability to alter specific image elements and iteratively refine selected regions through text-driven guidance. It also functions as an inpainting tool, filling missing or masked sections of an image with new content that blends naturally with
Chao Gong 1 · Dong Li 2 · Yingwei Pan 2 · Jingjing Chen 1,3✉️ · Ting Yao 2 · Tao Mei 2
Inpainting using Denoising Diffusion Probabilistic Models
Codebase to realistically insert objects into images via diffusion inpainting models with applications to anomaly segmentation and dataset extension as presented in Placing Objects in Context via Inpainting for Out-of-distribution Segmentation.
The main features of naver/poc are: Image Inpainting Models.
Open-source alternatives to naver/poc include: openai/glide-text2im — GLIDE is a generative model designed for text-to-image synthesis, image editing, and the contextual filling of masked… ascend-huawei/ascend-canada. charlesgong12/freeinpaint — Chao Gong 1 · Dong Li 2 · Yingwei Pan 2 · Jingjing Chen 1,3✉️ · Ting Yao 2 · Tao Mei** 2. crashmoon/progressive-generative-networks — Semantic Image Inpainting with Progressive Generative Networks. dengyecode/hourglassattention — python - m visdom.server python train.py --noflip --norotation --noaugment --imgfile yourdata --lr 1e-4 python… andreas128/repaint — Inpainting using Denoising Diffusion Probabilistic Models.
