alicepeter

SUSTechPOINTS

3D Point Cloud Annotation Platform for Autonomous Driving

extrinsic_lidar_camera_calibration

This is a package for extrinsic calibration between a 3D LiDAR and a camera, described in paper: Improvements to Target-Based 3D LiDAR to Camera Calibration. This package is used for Cassie Blue's 3D LiDAR semantic mapping and automation.

kalibr

The Kalibr visual-inertial calibration toolbox

ctf-writeups

CTF write-ups from the VulnHub CTF Team

visualDet3D

Official Repo for Ground-aware Monocular 3D Object Detection for Autonomous Driving / YOLOStereo3D: A Step Back to 2D for Efficient Stereo 3D Detection

MLofAndrew-Ng

吴恩达机器学习课程的讲义，欢迎大家一起学习

e200_opensource

Deprecated, please go to next generation Ultra-Low Power RISC-V Core https://github.com/riscv-mcu/e203_hbirdv2

linux-on-litex-vexriscv

Linux on LiteX-VexRiscv

VexRiscv

A FPGA friendly 32 bit RISC-V CPU implementation

vega

AutoML tools chain

PointTinyBenchmark

Point based and tiny object detection and localization code set of UCAS-VG

BLVD

Building A Large-scale 5D Semantics Benchmark for Autonomous Driving

Objectron

Objectron is a dataset of short, object-centric video clips. In addition, the videos also contain AR session metadata including camera poses, sparse point-clouds and planes. In each video, the camera moves around and above the object and captures it from different views. Each object is annotated with a 3D bounding box. The 3D bounding box describes the object’s position, orientation, and dimensions. The dataset contains about 15K annotated video clips and 4M annotated images in the following categories: bikes, books, bottles, cameras, cereal boxes, chairs, cups, laptops, and shoes

HRNet-Object-Detection

Object detection with multi-level representations generated from deep high-resolution representation learning (HRNetV2h). This is an official implementation for our TPAMI paper "Deep High-Resolution Representation Learning for Visual Recognition". https://arxiv.org/abs/1908.07919

HRNet-FCOS

High-resolution Networks for the Fully Convolutional One-Stage Object Detection (FCOS) algorithm

caffe-mobilenet

A caffe implementation of mobilenet's depthwise convolution layer.

CenterNet

Object detection, 3D detection, and pose estimation using center point detection:

ExtremeNet

Bottom-up Object Detection by Grouping Extreme and Center Points

cnn-explainer

Learning Convolutional Neural Networks with Interactive Visualization.

Random-Forest-Regressor-Sklearn

Random Forest Regressor with Scikit Learn for Heart Disease Prediction

kinematic3d

simpledet

A Simple and Versatile Framework for Object Detection and Instance Recognition

RTM3D

Unofficial PyTorch implementation of "RTM3D: Real-time Monocular 3D Detection from Object Keypoints for Autonomous Driving" (ECCV 2020)

pba

Efficient Learning of Augmentation Policy Schedules

ppdet

[BMVC-20] Official PyTorch implementation of PPDet.

NutShell

RISC-V SoC designed by students in UCAS

CrossStagePartialNetworks

Cross Stage Partial Networks

GP-MVS

Multi-View Stereo by Temporal Nonparametric Fusion

Real-time-self-adaptive-deep-stereo

Code for "Real-time self-adaptive deep stereo" - CVPR 2019 (ORAL)

EfficientDet

EfficientDet (Scalable and Efficient Object Detection) implementation in Keras and Tensorflow