In this research, we employ MTCNN to perform real-time facial bounding box regression for all sampled frames extracted from the video, without using associated facial landmark outputs. The detected facial regions determined by the bounding box regression vectors are cropped out for subsequent classific...
NoticeAny issue related to running the code has to be opened in thefaceswap Forum! About machine learning How does a computer know how to recognize/shape faces? How does machine learning work? What is a neural network? It's complicated. Here's a good video that makes the process understan...
pythonmachine-learningdeep-learningtensorflowface-recognitionfederated-learningdeepfakesdeepfake-detection UpdatedJul 25, 2022 sathya-ml/fsmetric Star0 Code Issues Pull requests Code used for the publication "A Quantitative Evaluation Framework of Video De-Identification Methods". ...
python train.py As you can see, the code is embarrassingly simple. I don't think it's worth...
改善面部动作,强化真实感,你值得拥有~_哔哩哔哩 (゜-゜)つロ 干杯~-bilibili 转自:https://www.bilibili.com/video/BV1y54y1s7VA?share_medium=web&share_source=baidu&b... 分享12 品质家园吧 pzjy315 马上消费与重庆师范大学共建实验室取得重大突破近日,马上消费与重庆师范大学共建的智慧金融与大数据分析...
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Running models is fairly cheap, but not free:it takes about 5–20X the duration of a video to create a swap when running on a GPU, e.g. a 1 minute 1080p video takes about 18 minutes to generate. A GPU helps speed up the core model, and also the face detection code (i.e. is...
Deepfakes extend the idea of video compositing with deep learning to make someone appear to say or do something they didn’t really say or do Credit: Thinkstock Deepfakes are media — often video but sometimes audio — that were created, altered, or synthesized with the aid of deep ...
All the code for this project can be found here:https://github.com/mjdargen/KK-Slider-Deepfake If you want to run the program immediately without setup, jump to step 7. Step 1: Video Capture In order to be able to cut together videos to make it look like KK Slider was speaking, I...
python cvit_prediction.py --p <video path> --f <number_of_frames> --d <dataset_type> --w <weights_path> --n <network_type> --fp16 <half_precision> E.g usage: python cvit_prediction.py --p sample__prediction_data --f 15 --n cvit2 --fp16 y ...