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iamlly/leetcode-master forked from HelloTeemo/leetcode-master

LeetCode 刷题攻略：200道经典题目刷题顺序，共60w字的详细图解，视频难点剖析，50余张思维导图，支持C++，Java，Python，Go，JavaScript等多语言版本，从此算法学习不再迷茫！🔥🔥 来看看，你会发现相见恨晚！🚀

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机器人小队/XTDrone forked from 肖昆/XTDrone

基于PX4、ROS和Gazebo的无人机通用仿真平台

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iamlly/IA-SSD

CVPR 2022 Oral | IA-SSD：用于3D LiDAR点云的高效基于点的检测器 我们研究了 3D LiDAR 点云的有效目标检测问题。为了降低内存和计算成本，现有的基于点的pipeline通常采用与任务无关的随机采样或最远点采样来逐步下采样输入点云，尽管并非所有点对目标检测任务都同等重要。特别是，对于目标检测器，前景点本质上比背景点更重要。

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iamlly/pct_torch

清华团队将Transformer用到3D点云分割上, pytorch版本

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iamlly/Fall-Detection-Dataset

FUKinect-Fall dataset was created using Kinect V1. The dataset includes walking, bending, sitting, squatting, lying and falling actions performed by 21 subjects between 19-72 years of age

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iamlly/Convolutional-Sequence-to-Sequence-Model-for-Human-Dynamics

Source code of paper "Convolutional Sequence to Sequence Model for Human Dynamics"

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iamlly/fall-msrgcn

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iamlly/openpifpaf_mpii

OpenPifPaf plugin to train and evaluate on the MPII pose dataset

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iamlly/MSRGCN

Official implementation of MSR-GCN (ICCV 2021 paper)

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iamlly/monoloco

A 3D vision library from 2D keypoints: monocular and stereo 3D detection for humans, social distancing, and body orientation.

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iamlly/SelfSAGCN

SelfSAGCN: Self-Supervised Semantic Alignment for Graph Convolution Network

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iamlly/st-gcn

Spatial Temporal Graph Convolutional Networks (ST-GCN) for Skeleton-Based Action Recognition in PyTorch

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iamlly/AlphaPose

AlphaPose Implementation in Pytorch along with the pre-trained wights

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iamlly/Human-Falling-Detect-Tracks

使用yolo、Alphapose、ST-GCN进行跌倒检测

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iamlly/CrowdPose

CrowdPose: Efficient Crowded Scenes Pose Estimation and A New Benchmark, CVPR 2019, Oral

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iamlly/openpifpaf_posetrack

OpenPifPaf plugin for Posetrack

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iamlly/mindspore forked from MindSpore/mindspore

关闭

MindSpore is a new open source deep learning training/inference framework that could be used for mobile, edge and cloud scenarios.

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iamlly/openpifpaf

openpifpaf2021最新骨骼点检测

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iamlly/Fall-Detection-with-CNNs-and-Optical-Flow

Repository containing the material required to reproduce the results of the paper "Vision-Based Fall Detection with Convolutional Neural Networks 论文：https://www.hindawi.com/journals/wcmc/2017/9474806/

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iamlly/Attention-boosted-deep-networks-for-video-classification

This is a implementation of integrating a simple but efficient attention block in CNN + bidirectional LSTM for video classification.