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annotated_deep_learning_paper_implementations

🧑‍🏫 59 Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠

audio-driven-talkingface-headpose

Code for "Audio-driven Talking Face Video Generation with Learning-based Personalized Head Pose"

audioprocessing

bendr

colossalai

Making big AI models cheaper, easier, and scalable

course-project---speech-driven-facial-animation

ECE 535 - Course Project, Deep Learning Framework

dann

pytorch implementation of Domain-Adversarial Training of Neural Networks

deepstory

Deepstory turns a text/generated text into a video where the character is animated to speak your story using his/her voice.

depressiontest-dev

fairseq

Facebook AI Research Sequence-to-Sequence Toolkit written in Python.

ffmpeg-builds

icassp2022-depression

Automatic Depression Detection: a GRU/ BiLSTM-based Model and An Emotional Audio-Textual Corpus

microsoft_speech_api

MimicSelf- STT, TTS, SDA-based lip-shaped video imitation pronunciation correction assistant

nepali-ai-anchor

Nepali AI Anchor Using LSTM & Pix2Pix. [ Itonics Hackathon 2019]

new_audio

speech-driven-animation

speech2face

Speech-Conditioned Face Generation with Deep Adversarial Networks

speechformer2

SpeechFormer++ in PyTorch

t2t-vit

ICCV2021, Tokens-to-Token ViT: Training Vision Transformers from Scratch on ImageNet

tensorface

This repo is deprecated, please use Deep Video Analytics which implements face recognition using TensorFlow and Facenet.

thesis

参考

voca

This codebase demonstrates how to synthesize realistic 3D character animations given an arbitrary speech signal and a static character mesh.

wav2lip

This repository contains the codes of "A Lip Sync Expert Is All You Need for Speech to Lip Generation In the Wild", published at ACM Multimedia 2020.

wav2lip-emotion

Wav2Lip-Emotion extends Wav2Lip to modify facial expressions of emotions via L1 reconstruction and pre-trained emotion objectives. We also propose a novel automatic evaluation for emotion modification corroborated with a user study.