zp1018's starred repositories

SKNet

Code for our CVPR 2019 paper: Selective Kernel Networks; See zhihu:https://zhuanlan.zhihu.com/p/59690223

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YOLOv3-model-pruning

在 oxford hand 数据集上对 YOLOv3 做模型剪枝(network slimming)

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PaddlePaddle_code

用PaddlePaddle和Tensorflow实现常用的深度学习算法

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MobileNet-YOLO

A caffe implementation of MobileNet-YOLO detection network

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mxnet-mtcnn

mtcnn mxnet C++ implementation

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Codes-for-Lane-Detection

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

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awesome-lane-detection

A paper list of lane detection.

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PerceptualSimilarity

LPIPS metric. pip install lpips

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SiamMask

[CVPR2019] Fast Online Object Tracking and Segmentation: A Unifying Approach

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caffe-windows

Configure Caffe in one hour for Windows users.

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Caffe-YOLOv3-Windows

A windows caffe implementation of YOLO detection network

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Caffe-YOLOv3-Windows

A windows caffe implementation of YOLO detection network

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pytorch-grad-cam

Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.

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PlotNeuralNet

Latex code for making neural networks diagrams

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darknet

YOLOv4 / Scaled-YOLOv4 / YOLO - Neural Networks for Object Detection (Windows and Linux version of Darknet )

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Augmentor

Image augmentation library in Python for machine learning.

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CVPR2019-Code

CVPR 2019 Paper with Code

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CVPR2019-Code

CVPR 2019 Paper with Code

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insightface

State-of-the-art 2D and 3D Face Analysis Project

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mtcnn

基于caffe的mtcnn训练实现,可以训练一个自己的有效的目标检测算法,非常容易非常简单,并且有配套的纯c++版本的mtcnn-light

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CenterNet

Codes for our paper "CenterNet: Keypoint Triplets for Object Detection" .

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RainsScriptLib

Useful scripts collection

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yolact

A simple, fully convolutional model for real-time instance segmentation.

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Caffe-Multi-Label

The caffe version support Multi-Label

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netron

Visualizer for neural network, deep learning and machine learning models

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instagan

InstaGAN: Instance-aware Image Translation (ICLR 2019)

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ReID-MGN

Simple pytorch unofficial implement of paper: Learning Discriminative Features with Multiple Granularities for Person Re-Identification

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