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mbsdtf's Projects

asff icon asff

yolov3 with mobilenet v2 and ASFF

cvt icon cvt

This is an official implementation of CvT: Introducing Convolutions to Vision Transformers.

darknet icon darknet

YOLOv4 - Neural Networks for Object Detection (Windows and Linux version of Darknet )

darknet_ros-1 icon darknet_ros-1

Robotics Operating System Package for Yolo v3 based on darknet with optimized tracking using Kalman Filter and Optical Flow.

fast-planner icon fast-planner

A Robust and Efficient Trajectory Planner for Quadrotors

g2o icon g2o

g2o: A General Framework for Graph Optimization

imu_utils icon imu_utils

A ROS package tool to analyze the IMU performance.

jetson-inference icon jetson-inference

Hello AI World guide to deploying deep-learning inference networks and deep vision primitives with TensorRT and NVIDIA Jetson.

kalibr icon kalibr

The Kalibr visual-inertial calibration toolbox

mixformer icon mixformer

[CVPR 2022 Oral] MixFormer: End-to-End Tracking with Iterative Mixed Attention

mmcv icon mmcv

Open MMLab Computer Vision Foundation

orb_slam icon orb_slam

A Versatile and Accurate Monocular SLAM

orb_slam2 icon orb_slam2

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

orb_slam3 icon orb_slam3

ORB-SLAM3: An Accurate Open-Source Library for Visual, Visual-Inertial and Multi-Map SLAM

orb_slam3-rgbd-inertial icon orb_slam3-rgbd-inertial

RGBD-inertial mode and its ROS interface was added to ORB_SLAM3. Two ROS interfaces Mono_inertial and Stereo_inertial were provided. Modified the loading vocabulary in a faster binary way.

orb_slam3-ros-interface icon orb_slam3-ros-interface

Two ROS interfaces Mono_inertial and Stereo_inertial were added to the ORB-SLAM3 . Modified the loading vocabulary in a faster binary way.

pangolin icon pangolin

Pangolin is a lightweight portable rapid development library for managing OpenGL display / interaction and abstracting video input.

remarkable icon remarkable

Remarkable - The Markdown Editor for Linux http://remarkableapp.github.io

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