wangq95

ASL

Official Pytorch Implementation of: "Asymmetric Loss For Multi-Label Classification"(ICCV, 2021) paper

AutoDeeplab

Pytorch Implementation the paper Auto-DeepLab Hierarchical Neural Architecture Search for Semantic Image Segmentation

AutoNL

Code for AutoNL on ImageNet (CVPR2020)

awesome-semantic-segmentation

:metal: awesome-semantic-segmentation

BANet

nonofficial implementation of paper "Boundary-Aware Network for Fast and High-Accuracy Portrait Segmentation"

caffe

Caffe: a fast open framework for deep learning.

KITTI_Dense_Depth

Generate dense depth map for monocular depth estimation task on KITTI dataset.

MeanShift

Meashift Tracking

NYUd2-Toolkit

Tools and tips to process NYUd v2 dataset for Monocular depth estimation task.

SiftGPU_Linux

Compiling and using SiftGPU on Linux OS.

wangq95/NYUd2-Toolkit

Tools and tips to process NYUd v2 dataset for Monocular depth estimation task.

wangq95/SiftGPU_Linux

Compiling and using SiftGPU on Linux OS.

wangq95/ASL

Official Pytorch Implementation of: "Asymmetric Loss For Multi-Label Classification"(ICCV, 2021) paper

wangq95/AutoDeeplab

Pytorch Implementation the paper Auto-DeepLab Hierarchical Neural Architecture Search for Semantic Image Segmentation

wangq95/AutoNL

Code for AutoNL on ImageNet (CVPR2020)

wangq95/BANet

nonofficial implementation of paper "Boundary-Aware Network for Fast and High-Accuracy Portrait Segmentation"

wangq95/crfasrnn-pytorch

PyTorch implementation of Conditional Random Fields as Recurrent Neural Networks (CRFasRNN), ICCV 2015 for semantic segmentation.

wangq95/DANet

Dual Attention Network for Scene Segmentation (CVPR2019)

wangq95/DeepLab-v3-plus-cityscapes

mIOU=80.02 on cityscapes. My implementation of deeplabv3+ (also know as 'Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation' based on the dataset of cityscapes).

wangq95/DeepLabV3Plus-Pytorch

DeepLabv3, DeepLabv3+ and pretrained weights on VOC & Cityscapes

wangq95/deeplearning-models

A collection of various deep learning architectures, models, and tips

wangq95/DFANet

reimpliment of DFANet: Deep Feature Aggregation for Real-Time Semantic Segmentation

wangq95/efficient_densenet_pytorch

A memory-efficient implementation of DenseNets

wangq95/EMANet

The code for Expectation-Maximization Attention Networks for Semantic Segmentation (ICCV'2019 Oral)

wangq95/ext_portrait_segmentation

wangq95/fanova

Functional ANOVA

wangq95/gan-compression

[CVPR 2020] GAN Compression: Efficient Architectures for Interactive Conditional GANs

wangq95/google_paper_download

wangq95/Inceptionv4_and_Inception-ResNetv2.PyTorch

A PyTorch implementation of Inception-v4 and Inception-ResNet-v2.

wangq95/LightNetPlusPlus

LightNet++: Boosted Light-weighted Networks for Real-time Semantic Segmentation

wangq95/mmaction

An open-source toolbox for action understanding based on PyTorch

wangq95/mobilenetv2.pytorch

72.8% MobileNetV2 1.0 model on ImageNet and a spectrum of pre-trained MobileNetV2 models

wangq95/models-1

Models and examples built with TensorFlow

wangq95/pretrained-models.pytorch

Pretrained ConvNets for pytorch: NASNet, ResNeXt, ResNet, InceptionV4, InceptionResnetV2, Xception, DPN, etc.

wangq95/pytorch-cifar100

Practice on cifar100(ResNet, DenseNet, VGG, GoogleNet, InceptionV3, InceptionV4, Inception-ResNetv2, Xception, Resnet In Resnet, ResNext,ShuffleNet, ShuffleNetv2, MobileNet, MobileNetv2, SqueezeNet, NasNet, Residual Attention Network, SENet)

wangq95/pytorch-deeplab-xception

DeepLab v3+ model in PyTorch. Support different backbones.

wangq95/pytorch-mobilenet-v3

MobileNetV3 in pytorch and ImageNet pretrained models

wangq95/pytorch_image_classification

image classification by pytorch

wangq95/Shufflenet-v2-Pytorch

Perfect implement. Model shared. x0.5 (Top1:60.646) and 1.0x (Top1:69.402).

wangq95/vision

Datasets, Transforms and Models specific to Computer Vision