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3d-resnets-pytorch

CVPR 2018:3D ResNets for Action Recognition

955.wlb

955 不加班的公司名单 - 工作 955，work–life balance (工作与生活的平衡)

annotations

:fork_and_knife: Annotations for the EPIC Kitchens Dataset.

c3d

动作识别框架，根据caffe改写，增加了一些工具。C3D is a modified version of BVLC caffe to support 3D ConvNets.

c3d-keras

train C3D with keras for action recognition

c3d-tensorflow

c3d-tensorflow-slim

Tensorflow小练习：C3D完成视频动作识别

caffe

Caffe: a fast open framework for deep learning.

caffe-mobilenet

A caffe implementation of mobilenet's depthwise convolution layer.

caffe-segnet

Implementation of SegNet: A Deep Convolutional Encoder-Decoder Architecture for Semantic Pixel-Wise Labelling

caffe_test

Caffe's usage

caffe_verifycode

Automatic recognition of verification code based on deep learning method

captcha_ml

基于machine learning识别验证码

cs-notes

:books: 技术面试必备基础知识、Leetcode 题解、后端面试、Java 面试、春招、秋招、操作系统、计算机网络、系统设计

deep-residual-networks

Deep Residual Learning for Image Recognition

deepdraw

Notebook example of how to generate class visualizations with Caffe

deeplab

deeplab_v3

Tensorflow Implementation of the Semantic Segmentation DeepLab_V3 CNN

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，50余万字。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

deeplearningtutorials

Deep Learning Tutorial notes and code. See the wiki for more info.

detect-cell-edge-use-unet

Unet

dstl-satellite-imagery-feature-detection

Place 18 solution for the Dstl feature detection kaggle challenge https://www.kaggle.com/c/dstl-satellite-imagery-feature-detection

egoconvnet

Code for CVPR 2016 paper "First Person Action Recognition Using Deep Learned Descriptors"

egotrajectoryfeatures

Code for Trajectory Aligned Features For First Person Action Recognition. Pattern Recognition (PR), 2017.

enet

ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation

examples

A set of examples around pytorch in Vision, Text, Reinforcement Learning, etc.

fcn.berkeleyvision.org

Fully Convolutional Networks for Semantic Segmentation by Jonathan Long*, Evan Shelhamer*, and Trevor Darrell. CVPR 2015 and PAMI 2016.

gpu_flow

GPU based optical flow extraction in OpenCV

hidden-two-stream

Caffe implementation for "Hidden Two-Stream Convolutional Networks for Action Recognition"

instance-segmentation-pytorch

Semantic Instance Segmentation with a Discriminative Loss Function in PyTorch