基于AI的图片/视频硬字幕去除、文本水印去除,无损分辨率生成去字幕、去水印后的图片/视频文件。无需申请第三方API,本地实现。AI-based tool for removing hard-coded subtitles and text-like watermarks from videos or Pictures.
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Updated
Jun 30, 2026 - Python
基于AI的图片/视频硬字幕去除、文本水印去除,无损分辨率生成去字幕、去水印后的图片/视频文件。无需申请第三方API,本地实现。AI-based tool for removing hard-coded subtitles and text-like watermarks from videos or Pictures.
Efficient & Generic Video Super-Resolution
A real-time silent speech recognition tool.
It is a re-implementation of paper named "Deep Video Super-Resolution Network Using Dynamic Upsampling Filters Without Explicit Motion Compensation" called VSR-DUF model. There are both training codes and test codes about VSR-DUF based tensorflow.
Official repository containing code and other material from the paper "Efficient Video Super-Resolution through Recurrent Latent Space Propagation" (https://arxiv.org/abs/1909.08080).
[Interspeech 2024] SyncVSR: Data-Efficient Visual Speech Recognition with End-to-End Crossmodal Audio Token Synchronization
[ECCV 2026] NanoVSR: Real-time video super-resolution on edge devices - official PyTorch implementation
This is an official implementation of Video Super-Resolution via a Spatio-Temporal Alignment Network.
Home Assistant integration for SystemAir SAVE ventilation units
A temporal video upscaler based on SPAN
ICIP2024 challenge for 360 super resolution
HiRN: Hierarchical Recurrent Neural Network for Video Super-Resolution (VSR) using Two-Stage Feature Evolution - Official Repository (Applied Soft Computing)
Group-based Bi-Directional Recurrent Wavelet Neural Network for Efficient Video Super-Resolution (VSR) - Official Repository (Pattern Recognition Letters)
HiRN: Hierarchical Recurrent Neural Network for Video Super-Resolution (VSR) using Two-Stage Feature Evolution - Official Repository (Applied Soft Computing)
Speaker-Independent Speech Recognition using Visual Features
Group-based Bi-Directional Recurrent Wavelet Neural Network for Efficient Video Super-Resolution (VSR) - Official Repository (Pattern Recognition Letters)
🚀 SynthAVSR is a research framework for training and evaluating audiovisual speech recognition (AVSR) models using synthetic data — with a focus on low-resource languages like Spanish and Catalan.
🗑️ Remove unwanted data from CSV files with ease, preserving your source while saving output neatly in the project’s outputs folder.
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