yktangac
Hello, my name is Hugo. Github is the best place to learn! Looking forward to have different projects in future.
yktangac's Stars
bighuang624/LeetCode-everyday
每天一题 LeetCode | workin' everyday~Hustle everyday~LeetCode everyday~yuh yuh yuh
mindsdb/mindsdb
The platform for building AI from enterprise data
TianhaoFu/Awesome-3D-Object-Detection
Papers, code and datasets about deep learning for 3D Object Detection.
LeCoupa/awesome-cheatsheets
👩💻👨💻 Awesome cheatsheets for popular programming languages, frameworks and development tools. They include everything you should know in one single file.
ruanyf/simple-bash-scripts
A collection of simple Bash scripts
huawei-noah/SMARTS
Scalable Multi-Agent RL Training School for Autonomous Driving
huawei-noah/Efficient-AI-Backbones
Efficient AI Backbones including GhostNet, TNT and MLP, developed by Huawei Noah's Ark Lab.
leandromoreira/ffmpeg-libav-tutorial
FFmpeg libav tutorial - learn how media works from basic to transmuxing, transcoding and more. Translations: 🇺🇸 🇨🇳 🇰🇷 🇪🇸 🇻🇳 🇧🇷
edkolev/tmuxline.vim
Simple tmux statusline generator with support for powerline symbols and statusline / airline / lightline integration
open-mmlab/mmdetection
OpenMMLab Detection Toolbox and Benchmark
RunaCapital/awesome-oss-alternatives
Awesome list of open-source startup alternatives to well-known SaaS products 🚀
coding-horror/basic-computer-games
An updated version of the classic "Basic Computer Games" book, with well-written examples in a variety of common MEMORY SAFE, SCRIPTING programming languages. See https://coding-horror.github.io/basic-computer-games/
fastai/fastbook
The fastai book, published as Jupyter Notebooks
dive-into-machine-learning/dive-into-machine-learning
Free ways to dive into machine learning with Python and Jupyter Notebook. Notebooks, courses, and other links. (First posted in 2016.)
apchenstu/mvsnerf
[ICCV 2021] Our work presents a novel neural rendering approach that can efficiently reconstruct geometric and neural radiance fields for view synthesis.
sfzhang15/ATSS
Bridging the Gap Between Anchor-based and Anchor-free Detection via Adaptive Training Sample Selection, CVPR, Oral, 2020
JonathonLuiten/TrackEval
HOTA (and other) evaluation metrics for Multi-Object Tracking (MOT).
QingyongHu/VISO
[IEEE TGRS 2021] Detecting and Tracking Small and Dense Moving Objects in Satellite Videos: A Benchmark
kkroening/ffmpeg-python
Python bindings for FFmpeg - with complex filtering support
pylabel-project/pylabel
Python library for computer vision labeling tasks. The core functionality is to translate bounding box annotations between different formats-for example, from coco to yolo.
ifzhang/ByteTrack
[ECCV 2022] ByteTrack: Multi-Object Tracking by Associating Every Detection Box
ultralytics/yolov5
YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite
TRI-ML/packnet-sfm
TRI-ML Monocular Depth Estimation Repository
TRI-ML/realtime_panoptic
Official PyTorch implementation of CVPR 2020 Oral: Real-Time Panoptic Segmentation from Dense Detections
TRI-ML/permatrack
Implementation for Learning to Track with Object Permanence
aim-uofa/AdelaiDet
AdelaiDet is an open source toolbox for multiple instance-level detection and recognition tasks.
dvlab-research/DSGN
DSGN: Deep Stereo Geometry Network for 3D Object Detection (CVPR 2020)
PaddlePaddle/PaddleDetection
Object Detection toolkit based on PaddlePaddle. It supports object detection, instance segmentation, multiple object tracking and real-time multi-person keypoint detection.
dbklim/docker_image_with_cuda10_cudnn7
Dockerfiles and manual for easy build of docker image with CUDA10.X and cuDNN7.6 to run TensorFlow/PyTorch on the nvidia GPU in docker-container.
fcjian/TOOD
TOOD: Task-aligned One-stage Object Detection, ICCV2021 Oral