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complex_pf

RES via complex-valued DNN

computelibrary

The Compute Library is a set of computer vision and machine learning functions optimised for both Arm CPUs and GPUs using SIMD technologies.

conferencingspeech2021

Conferencing Speech Challenge

conformer

PyTorch implementation of "Conformer: Convolution-augmented Transformer for Speech Recognition" (INTERSPEECH 2020)

conv-tasnet

conv_arithmetic

A technical report on convolution arithmetic in the context of deep learning

cppcon2019

Slides and other materials from CppCon 2019

cvpytorch

CvPytorch is an open source COMPUTER VISION toolbox based on PyTorch.

dall-e

PyTorch package for the discrete VAE used for DALL·E.

db-aiat

A dual-branch attention-in-attention transformer (dubbed DB-AIAT) to focus on both coarse and fine-grained regions of spectrum in parallel, i.e., spectral magnitude and lost complex spectral details. The source code will be released soon

dbt-net

The audio demos with respect to the paper "DBT-Net: Dual-branch federative magnitude and phase estimation with attention-in-attention transformer for monaural speech enhancement" are provided (submitted to TASLP). The code will also be released soon.

ddaec

deadline

other

deep-learning-with-tensorflow-book

深度学习入门开源书，基于TensorFlow 2.0案例实战。Open source Deep Learning book, based on TensorFlow 2.0 framework.

deep-non-linear-filter

deep_complex_networks

Implementation related to the Deep Complex Networks

deep_sort

Simple Online Realtime Tracking with a Deep Association Metric

deepcomplexcrn

deepfilternet

Noise supression using deep filtering

deeplearning-500-questions

深度学习500问，以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述，以帮助自己及有需要的读者。 全书分为18个章节，近30万字。由于水平有限，书中不妥之处恳请广大读者批评指正。 未完待续............ 如有意合作，联系[email protected] 版权所有，违权必究 Tan 2018.06

deepped

Convolutional Neural Networks for Pedestrian Detection

demucs

Code for the paper Hybrid Spectrogram and Waveform Source Separation

denoiser

Real Time Speech Enhancement in the Waveform Domain (Interspeech 2020)We provide a PyTorch implementation of the paper Real Time Speech Enhancement in the Waveform Domain. In which, we present a causal speech enhancement model working on the raw waveform that runs in real-time on a laptop CPU. The proposed model is based on an encoder-decoder archi

descript-audio-codec

State-of-the-art audio codec with 90x compression factor. Supports 44.1/24 kHz mono/stereo audio.

design-patterns-gof

Working code for the Design Patterns book from the Gang of Four.

designaudiopriors

A Novel U-Net Prior for Unsupervised Audio Restoration

dgd_person_reid

Domain Guided Dropout for Person Re-identification

diffusion-models-papers-survey-taxonomy

Diffusion model papers, survey, and taxonomy

dive-into-dl-pytorch

本项目将《动手学深度学习》(Dive into Deep Learning)原书中的MXNet实现改为PyTorch实现。

dive-into-dl-tensorflow2.0

本项目将《动手学深度学习》(Dive into Deep Learning)原书中的MXNet实现改为TensorFlow 2.0实现，项目已得到李沐老师的认可