🔥 CNN for Watermark Removal using Deep Image Prior with Pytorch 🔥.

Open-source watermark segmentation by DiffusionDynamics.ai and clear.photo. Harness deep learning plus synthetic data augmentation in PyTorch to detect logos/text precisely. This minimal code references top research for robust, adaptable watermark removal.

This is an official pytorch implementation for "DENet: Disentangled Embedding Network for Visible Watermark Removal" (AAAI23).

🔥 Implementing Deep Image Prior for removing watermarks from images with Pytorch 🔥. This paper shows that the structure of a generator alone is sufficient to provide enough low-level image statistics without any learning. Thus most of the image restoration tasks, for example, denoising, super-resolution, artefacts removal, watermark removal etc can be done with highly realistic results without any training.

Pytorch Implementation of the Watemark Removal repository

Open-source watermark segmentation by DiffusionDynamics.ai and clear.photo. Harness deep learning plus synthetic data augmentation in PyTorch to detect logos/text precisely. This minimal code references top research for robust, adaptable watermark removal.

SORA2 Watermark Remover — AI-powered desktop application for video enhancement and visible watermark removal from Sora 2 generated content with TensorFlow/PyTorch neural inpainting, batch frame processing, CUDA GPU acceleration, and Tkinter GUI interface

CNN for Watermark Removal using Deep Image Prior with Pytorch

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PyTorch implementation of watermark removal feature

Watermark removal using U-Net in Pytorch

from https://github.com/braindotai/Watermark-Removal-Pytorch

Transformer Architecture for Watermark Removal (CTU FIT thesis, PyTorch based)

AI-based watermark removal tool using a custom-trained U-Net model in PyTorch. Processes all images in a folder and outputs clean versions.