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!用累积的子图做全局重定位提升鲁棒性
cartographer,cartographer_ros,ceres_solver,protobuf
carto和carto_ros用cmake统一,这样可以在IDE中对carto的代码进行debug
级联细化网格用于点云补全Cascaded Refinement Network for Point Cloud Completion (CVPR 2020)
!一种利用雷达和摄像机数据进行3D目标检测的中间融合方法:CenterFusion: Center-based Radar and Camera Fusion for 3D Object Detection
!maYOLACT实时实例分割检测器:CenterMask : Real-Time Anchor-Free Instance Segmentation, in CVPR 2020
!本文研究了从单视角RGB-D观测中同时进行多物体3D重建、6D姿势和尺寸估计的复杂任务Pytorch code for ICRA'22 paper: "Single-Shot Multi-Object 3D Shape Reconstruction and Categorical 6D Pose and Size Estimation"
西交&商汤-基于向心偏移的anchor-free目标检测网络centripetalnet:Source codes of "CentripetalNet: Pursuing High-quality Keypoint Pairs for Object Detection"
!路径规划-一种新的时空混合状态A*算法作为单智能体路径规划算法,生成满足运动约束和时空约束的路径!:An Efficient Multi-Agent Path Finding Solver for Car-Like Robots
用CLion+Cmake同时管理cartographer和cartographer_ros,实现对carto的编译、debug单步调试
个人的clion软件配置
!!!CLIPPER:基于图论的一致性连接,剪枝和匹配错误矫正框架(数据关联)graph-theoretic framework for robust pairwise data association
Real-time motion from structure
!!一种基于相关熵以及双向匹配的鲁棒且准确的配准方法:[IROS2020] CoBigICP: COrrentropy based BIdirectional Generalized ICP
《剑指Offer》第二版源代码
!!!基于点云强度信息增强来补偿的 LIO--可运行于长廊环境,平坦地面,半开放环境等退化场景
Visual-SLAM based on COLMAP API
!视频实例分割-新特征聚合方法CompFeat,利用了时空间的上下文信息在帧级和对象级细化特征:CompFeat: Comprehensive Feature Aggregation for Video Instance Segmentation (AAAI 2021)
!!新网络Conformer=CNN+Transformer,依靠特征耦合单元(FCU),以交互的方式在不同分辨率下融合局部特征表示和全局特征表示
!!!超越Transformer的纯卷积架构:Code release for ConvNeXt model
!!基于Transformer的图像匹配网络: Code release for "COTR: Correspondence Transformer for Matching Across Images"
!!一种利用语义来全局定位的实时方法
CT-LIO: Continuous-Time LiDAR-Inertial Odometry
CTLO: Continuous-Time LiDAR Odometry
大功率电机foc控制板+算法
!!用于LiDAR点云分割的圆柱形非对称3D卷积网络Rank 1st in the leaderboard of SemanticKITTI semantic segmentation (both single-scan and multi-scan) (Nov. 2020) (CVPR2021 Oral)
单阶段分割跟踪器:思路简洁,训练快,占显存小,1080TI上为25FPS:D3S - Discriminative Single Shot Segmentation Tracker (CVPR 2020)
Code for the paper "Low Latency Automotive Vision with Event Cameras", published in Nature
!!!多激光雷达同时定位建图以及外参自标定的分布式框架(多个固态激光MID40)
深度学习500问,以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述,以帮助自己及有需要的读者。 全书分为18个章节,近30万字。由于水平有限,书中不妥之处恳请广大读者批评指正。 未完待续............ 如有意合作,联系[email protected] 版权所有,违权必究 Tan 2018.06
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