scott-mao Goto Github PK

cavaface.pytorch

:beers: :rocket: :city_sunset: face recognition project(pytorch)

cbdnet-pytorch

Unofficial PyTorch implementation of CBDNet.

cbnetv2

ccp

CCPrune: Collaborative Channel Pruning for Learning Compact Convolutional Networks

cdiou-cdiouloss

🔥CDIoU and CDIoU loss is like a convenient plug-in that can be used in multiple models. CDIoU and CDIoU loss have different excellent performances in several models such as Faster R-CNN, YOLOv4, RetinaNet and . There is a maximum AP improvement of 1.9% and an average AP of 0.8% improvement on MS COCO dataset, compared to traditional evaluation-feedback modules. Here we just use as an example to illustrate the code.

centerdet

centerpose

Single-Stage Keypoint-based Category-level Object Pose Estimation from an RGB Image (ICRA 2022)

central-filter

cerl

"CERL: Coordinated Enhancement for Real-World Low-Light Noisy Images" by Zeyuan Chen, Yifan Jiang, Zhangyang Wang and Dong Liu

cfme

Object Tracking in Satellite Videos by Improved Correlation Filters With Motion Estimations, TGRS

cfnet

CFNet: Cascade and Fused Cost Volume for Robust Stereo Matching（CVPR2021）

cgacd

Correlation-Guided Attention for Corner Detection Based Visual Tracking (CVPR2020)

channel_pruning_lasso

channel pruning for accelerating very deep neural networks

chexnet-model-compression

Official Implementation of "CheXNet Model Compression for Pneumonia detection on low edged device"

chineseocr_lite

超轻量级中文ocr，支持竖排文字识别, 支持ncnn、mnn、tnn推理 ( dbnet(1.8M) + crnn(2.5M) + anglenet(378KB)) 总模型仅4.7M

chip_neurips2021

Code for CHIP: CHannel Independence-based Pruning for Compact Neural Networks (NeruIPS 2021).

chipnet

Official implementation "ChipNet: Budget-Aware Pruning with Heaviside Continuous Approximations"

chr10003566.github.io

Private Blog

cia-ssd

CIA-SSD: Confident IoU-Aware Single Stage Object Detector From Point Cloud, AAAI 2021.

classification

图像识别框架(轻量级、模块化、可扩展)

clnet

cluster-contrast-reid

clustering-channel-pruning

Our paper is accepted by IJCNN 2021--Energy-saving CNN with Clustering Channel Pruning

cmake-demo

《CMake入门实战》源码

cmt-threaded-on-windows

Implementation of CMT on WIndows with Multi-threading for Multiple-object Tracking.

co-prune

Codes for accepted paper "Cooperative Pruning in Cross-Domain Deep Neural Network Compression" in IJCAI 2019.

coconv

codes-for-lane-detection

Learning Lightweight Lane Detection CNNs by Self Attention Distillation (ICCV 2019)

compress_yolo

对yolo模型进行网络压缩、修剪等实验

computelibrary

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