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rotorliu's Projects

cocoapi icon cocoapi

COCO API - Dataset @ http://cocodataset.org/

colmap icon colmap

COLMAP - Structure-from-Motion and Multi-View Stereo

conv_arithmetic icon conv_arithmetic

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

convnetjs icon convnetjs

Deep Learning in Javascript. Train Convolutional Neural Networks (or ordinary ones) in your browser.

coreclr icon coreclr

This repo contains the .NET Core runtime, called CoreCLR, and the base library, called mscorlib. It includes the garbage collector, JIT compiler, base .NET data types and many low-level classes.

cpp-lru-cache icon cpp-lru-cache

Simple and reliable LRU cache for c++ based on hashmap and linkedlist

crl icon crl

Implementation of the paper "Cascade Residual Learning: A Two-stage Convolutional Neural Network for Stereo Matching"

ctpn icon ctpn

Detecting Text in Natural Image with Connectionist Text Proposal Network

cuda-samples icon cuda-samples

Samples for CUDA Developers which demonstrates features in CUDA Toolkit

cvat icon cvat

Powerful and efficient Computer Vision Annotation Tool (CVAT)

cyclegan icon cyclegan

Software that can generate photos from paintings, turn horses into zebras, perform style transfer, and more.

dab icon dab

Dataset Annotation Builder

dali icon dali

A library containing both highly optimized building blocks and an execution engine for data pre-processing in deep learning applications

darknet icon darknet

Windows version of Yolo Convolutional Neural Networks

data icon data

PCD files for tutorials, examples, or PCL-related applications

dcos icon dcos

DC/OS Build and Release tools

dcos-iot-demo icon dcos-iot-demo

This project demonstrates how to configure a full stack geo-enabled Internet of Things (IoT) solution using Mesosphere's open sourced Data Center Operating System (DC/OS) using Docker containerization and frameworks for Mesos including Marathon, Kafka, Spark, and Elasticsearch.

deep-learning-papers icon deep-learning-papers

Papers about deep learning ordered by task, date. Current state-of-the-art papers are labelled.

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