1171257311's repositories
SuperPoint_SLAM
SuperPoint + ORB_SLAM2
caffe
Caffe: a fast open framework for deep learning.
caffe-segnet-cudnn5
This repository was a fork of BVLC/caffe and includes the upsample, bn, dense_image_data and softmax_with_loss (with class weighting) layers of caffe-segnet (https://github.com/alexgkendall/caffe-segnet) to run SegNet with cuDNN version 5.
dataset-tools
Computer-vision dataset tools that I am using or working on
DeepLabV3Plus-Pytorch
DeepLabv3, DeepLabv3+ and pretrained models on VOC & Cityscapes
detect-slam
reimplementation of paper Detect-SLAM: Making Object Detection and SLAM Mutually Beneficial
Dynamic_ORB_SLAM2
Visual SLAM system that can identify and exclude dynamic objects.
EdgeNets
This repository contains the source code of our work on designing efficient CNNs for computer vision
ENet
ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation
evo
Python package for the evaluation of odometry and SLAM
LeetCode
LeetCode刷题记录
maskfusion
MaskFusion: Real-Time Recognition, Tracking and Reconstruction of Multiple Moving Objects
MobileNet-Caffe
Caffe Implementation of Google's MobileNets (v1 and v2)
opencv_extra
OpenCV extra data
ORB-SLAM-RGBD-with-Octomap
ORB_SLAM with Octomap
picgo
图床
pytorch
Tensors and Dynamic neural networks in Python with strong GPU acceleration
resnet_libtorch
This repository saves resnet from PyTorch in TorchScript and loads it in libtorch for C++ deployment.
RGBD-Slam-Semantic-Seg-DeepLab
The package is common Slam combined with DeepLab-V2-CRF Library.
SuperPointPretrainedNetwork
PyTorch pre-trained model for real-time interest point detection, description, and sparse tracking (https://arxiv.org/abs/1712.07629)
VINS-FUSION-leanrning
VINS-FUSION中文注释版.目前网络上对于VINS-mono的代码已经有很多讲解和注释了，但是对于VINS-FUSION（以下简称VF）的注释还是很少的，刚好本人最近也正在学习VIO的相关知识，所以对VF按照程序执行顺序进行了十分详细的注释，同时为了和大家进行交流学习，所以把相关注释代码进行开源。因水平有限，错误肯定不少，还请各位大佬们指正。
VINS-Mono-Optimization
实现点线紧耦合优化的VINS-Mono
VINS_Mono_note
VINS-Mono 个人注释
vio_data_simulation
Generate imu data and feature in camera frame. You can use this data to test your VINS.
yolact
A simple, fully convolutional model for real-time instance segmentation.