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blenderproc

A procedural Blender pipeline for photorealistic training image generation

crawler_notes

cuboid-fitting-ransac

RanSaC based cuboid fitting heuristic

dlib

C++ library with several utilities

dloopdetector

A loopdetector descrided in DBoW2. This project modify the vocabulary loading procedure (load from yml to load from txt) to accelerate loading speed.

general_3d

A project to implement some state-of-the-art 3D network architecture.

gittalk-comments

store gittalk comments

graph-neural-network

collect some papers about Graph Neural Networks(GNN)

java_notes

kalmanfiltertutorial

卡尔曼滤波的示例代码

lio-sam

LIO-SAM: Tightly-coupled Lidar Inertial Odometry via Smoothing and Mapping

mit6.828-notes

notes when learning mit6.828 course

opencv-bazel

Minimum example to show how to build bazel project which depends on opencv

orb_slam2

Real-Time SLAM for Monocular, Stereo and RGB-D Cameras, with Loop Detection and Relocalization Capabilities

orb_slam_tracking

Tracking thread in ORB_SLAM, provides multiple demo to run different steps in tracking thread

pointcloudclustering

Compare the time cost of vanilla EuclideanClusterExtraction in pcl and Fast Euclidean Clustering algorithm

protobuf-bazel

Minimum example to using protocal buffer in bazel c++ project

pytorch_sdmaskrcnn

A pytorch version of sd-maskrcnn and maskrcnn

rknn_model_zoo

rosbag2

self6dpp

Self6D++: Occlusion-Aware Self-Supervised Monocular 6D Object Pose Estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) 2021.

simple-lio-sam

Code for simplified LIO-SAM

slam2d_g2o_example

Split tutorial_slam2d example from g2o source project. Compiled as an normal project dependent on g2o.

some-memo

一些语句的备忘：Markdown、ubuntu操作、nvidia操作等

theme-next-docs

📖 The documentation for NexT.

topics-notes

some notes when reading papers

trimesh

Python library for loading and using triangular meshes.

ubuntu-setting

video-nonlocal-net

Non-local Neural Networks for Video Classification

video_classification_pytorch

This repository includes some classical network architecture of video classification(action recognition). Because of the scale of Kinetics, most of the architectures in this repo have not be tested on kenetics. But the training loss curve seems normal in the training procedure.