03 2024 档案
摘要:https://blog.csdn.net/u011863024/article/details/132378433
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摘要:https://blog.csdn.net/lhl_blog/article/details/123553686
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摘要:https://zhuanlan.zhihu.com/p/618229430?utm_id=0
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摘要:https://blog.csdn.net/qq_39149619/article/details/131931773 https://blog.csdn.net/qq_39149619/article/details/131882664?spm=1001.2014.3001.5501
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摘要:https://www.jb51.net/article/229498.htm #!/usr/bin/env python3 # -*- coding: utf-8 -*- """ Created on Mon May 7 21:45:37 2018 @author: lps """ import
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摘要:https://blog.csdn.net/qq_45605440/article/details/127672128
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摘要:1 #include<iostream> using namespace std; void quickSort(int arr[], int begin, int end) { if (begin >= end) return; int left = begin; int right = end;
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摘要:https://zhuanlan.zhihu.com/p/591349481
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摘要:https://www.guyuehome.com/44312 https://blog.csdn.net/BIT_HXZ/article/details/123539476
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摘要:https://blog.csdn.net/Elon15/article/details/126085981 https://zhuanlan.zhihu.com/p/550677537
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摘要:https://blog.csdn.net/Strengthennn/article/details/136615677
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摘要:https://zhuanlan.zhihu.com/p/457742309?utm_id=0
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摘要:https://blog.csdn.net/qq_39149619/article/details/131931773
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摘要:https://www.jianshu.com/p/ec7249f1ba9a
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摘要:CMakeLists.txt的写法 CMakeLists.txt cmake_minimum_required(VERSION 3.9)#Cmake最低版本 #project(demo LANGUAGES CXX CUDA) #这个写法也是可以的 project(demo) enable_langu
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摘要:https://blog.51cto.com/u_16162011/6485510
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摘要:https://blog.csdn.net/weixin_39059031/article/details/109803742
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摘要:https://blog.csdn.net/boon_228/article/details/125925739
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摘要:import numpy as np import open3d as o3d bin_file = "" xyz = np.fromfile(bin_filem, dtype= np.float32).reshape(-1,5)[:, 0:3] pcd = o3d.geometry.PointCl
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摘要:https://github.com/SmallMunich/nutonomy_pointpillars/blob/master/second/pytorch/models/pointpillars.py
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摘要:GitHub - HaohaoNJU/CenterPoint: TensorRT deployment for CenterPoint Lidar Detection Model. CenterPoint-TensorRT部署 - 知乎 (zhihu.com)
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摘要:https://zhuanlan.zhihu.com/p/654466989
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摘要:https://blog.csdn.net/weixin_43253464/article/details/120669293 https://zhuanlan.zhihu.com/p/594410108?utm_id=0
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摘要:https://blog.csdn.net/baller_Tionary/article/details/134080350
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摘要:https://blog.csdn.net/weixin_40826634/article/details/127836169
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摘要:常用的 3D 目标检测模型有: VoxelNet:基于卷积神经网络的模型,可以进行立体感知和目标检测。 PointPillars:利用点云数据进行立体感知和目标检测的模型。 AVOD(Average Viewpoint Feature Aggregation for 3D Object Detect
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摘要:https://mmdetection3d.readthedocs.io/zh-cn/latest/advanced_guides/supported_tasks/vision_det3d.html
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摘要:python实现 import os import struct import numpy as np from nuscenes.nuscenes import NuScenes from nuscenes.utils.data_classes import LidarPointCloud imp
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摘要:https://blog.csdn.net/weixin_44330367/article/details/132098586
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摘要:https://blog.csdn.net/L1uminous/article/details/130858746
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摘要:https://blog.csdn.net/zoolybo/article/details/135749479
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摘要:自注意力机制(Self-Attention Mechanism)是一种在自然语言处理和计算机视觉等领域中广泛使用的技术,它可以帮助模型在处理序列数据时更好地理解上下文信息。 在自注意力机制中,输入序列被表示为一组向量(比如说在自然语言处理中,可以将一句话中的每个单词表示为一个向量),每个向量都被称为
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