jieli1990 Goto Github PK

amos-slam

This work proposes an anti-dynamics two-stage RGB-D SLAM approach that surpasses current state-of-the-art (SOTA) dynamic SLAM techniques on public datasets and demonstrates its robustness through extensive experiments using public datasets and real-world scenarios.

anyloc

Official Code Repository for AnyLoc

bev-joint

将每一帧的bev矢量图拼接起来（实习项目）

bililive-go

一个直播录制工具

bililiverecorder

B站录播姬 | BiliBili Stream Recorder | 哔哩哔哩直播录制

biliup

全自动录播、直播录制、分p投稿工具，支持twitch、ytb频道搬运。

chatglm-6b

ChatGLM-6B：开源双语对话语言模型 | An Open Bilingual Dialogue Language Model

chatglm-flask-api

ChatGLM-flask-api 简单的请求即可与ChatGLM对话

chatglm-mnn

Pure C++, Easy Deploy ChatGLM-6B.

chatrwkv-flask-api

chinese-llama-alpaca

中文LLaMA&Alpaca大语言模型+本地CPU/GPU训练部署 (Chinese LLaMA & Alpaca LLMs)

cluepretrainedmodels

高质量中文预训练模型集合：最先进大模型、最快小模型、相似度专门模型

computervision

https://www.youtube.com/watch?v=f-Ibri14KMY&ab_channel=NicolaiNielsen-ComputerVision%26AI

concept-graphs

Official code release for ConceptGraphs

cvo-slam

A Robust Keyframe-based Visual SLAM for RGB-D Cameras in Challenging Scenarios

ddpff

Plane Segmentation Using Depth Dependent Flood Fill

depth-anything

Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data

dm-vio

Source code for the paper DM-VIO: Delayed Marginalization Visual-Inertial Odometry

dynamicmap_benchmark

[ITSC'23] Dynamic map benchmark, open-sourced all the methods and datasets in the paper.

dynavins

DynaVINS : A Visual-Inertial SLAM for Dynamic Environments

elas

Efficient Large-scale Stereo Matching.

eplf-vins

fastllm

纯c++的全平台llm加速库，支持python调用，chatglm-6B级模型单卡可达10000+token / s，支持glm, llama, moss基座，手机端流畅运行

fastorb-slam

Fast ORB-SLAM without Keypoint Descriptors

fastsam

Fast Segment Anything

gdrnpp_bop2022

PyTorch Implementation of GDRNPP, winner (most of the awards) of the BOP Challenge 2022 at ECCV'22

gpt4all

gpt4all: open-source LLM chatbots that you can run anywhere

gqlite

graph database lite

graspkpnet

jieli1990

Config files for my GitHub profile.