tracking segments 1843e

Center-based 3D Object Detection and Tracking

zotero-key: A37ALEJ3 zt-attachments: - "280" title: Center-based 3D Object Detection and Tracking citekey: yinCenterbased3DObject2021 Center-based 3D ......

An improved LSTM-based model for identifying high working intensity load segments of the tractor load spectrum

一区top Computers and Electronics in Agriculture 题目: “基于改进 lstm 的拖拉机载荷谱高工作强度载荷段识别模型” (pdf) “An improved LSTM-based model for identifying high working in ......

Learning Dynamic Query Combinations for Transformer-based Object** Detection and Segmentation论文阅读笔记

Motivation & Intro 基于DETR的目标检测范式(语义分割的Maskformer也与之相似)通常会用到一系列固定的query,这些query是图像中目标对象位置和语义的全局先验。如果能够根据图像的语义信息调整query,就可以捕捉特定场景中物体位置和类别的分布。例如,当高级语义显示图 ......

1.9 Rotated Multi-Scale Interaction Network for Referring Remote Sensing Image Segmentation 基于语义分割遥感图像的模型

Rotated Multi-Scale Interaction Network for Referring Remote Sensing Image Segmentation 参考遥感图像分割的旋转多尺度交互网络 参考遥感图像分割 (RRSIS)是一个新的挑战,它结合了计算机视觉和自然语言处理,通过 ......

Segment Anything(SAM)环境安装&代码调试

引子 Segment Anything是前阵子大火的CV领域模型,之前也有尝试,只是没有整理。OK,让我们开始吧 一、拉取下载docker镜像 docker pull cnstark/pytorch:2.0.1-py3.9.17-cuda11.8.0-ubuntu20.04 二、安装SAM环境 do ......
Anything Segment 代码 环境 SAM

C - Loong Tracking

C - Loong Tracking 题目传送门 https://atcoder.jp/contests/abc335/tasks/abc335_c 思路 贪吃蛇,头部不断更新, 原来的头部会变成颈部,颈部变成胸膛,..., 原来的尾部删除。 采用双端队列, 头部 根据 头部做更新 尾部删除。 Co ......
Tracking Loong

ABC335 C - Loong Tracking

ABC335 C - Loong Tracking \(\mathtt{TAG}\): STL,模拟 \(\mathtt{APPRAIS}\):STL の 巧用 前置知识 deque 可以下表 \(O(1)\) 访问。 deque 可以删除队尾队首元素,在队尾队首插入元素。 First. 修改 设 ......
Tracking Loong ABC 335

A Long read hybrid error correction algorithm based on segmented pHMM

A Long read hybrid error correction algorithm based on segmented pHMM 2023/12/15 11:06:36 The "Long read hybrid error correction algorithm based on se ......
correction algorithm segmented hybrid error

【模板】李超线段树 / [HEOI2013] Segment

李超线段树是一种用于维护平面直角坐标系内线段关系的数据结构,插入直线/线段,支持查询单点极值 李超树的经典应用是斜率优化,可以看下这篇文章 李超线段树没有用懒标记实现区间修改,而用的是标记永久化 其实标记永久化与我们对lazy标记的理解非常相同,可以看看LYD蓝书上对标记永久化的解释,都是累积某个节 ......
线段 模板 Segment HEOI 2013

A Long read hybrid error correction algorithm based on segmented pHMM 基于pHMM的DNA序列分析与错误修正方法研究

基于pHMM的DNA序列分析与错误修正方法研究 这篇论文主要内容是关于DNA序列分析中的错误纠正方法。论文提出了一种基于概率隐马尔可夫模型(pHMM)的错误纠正方法。首先,通过SR-LR对齐和基于短读序列对齐的预处理步骤,对DNA序列进行处理。然后,利用pHMM构建了一个隐藏的马尔可夫模型,并进行前 ......

SegNeXt: Rethinking Convolutional Attention Design for Semantic Segmentation

SegNeXt: Rethinking Convolutional Attention Design for Semantic Segmentation * Authors: [[Meng-Hao Guo]], [[Cheng-Ze Lu]], [[Qibin Hou]], [[Zhengning ......

CCNet: Criss-Cross Attention for Semantic Segmentation

CCNet: Criss-Cross Attention for Semantic Segmentation * Authors: [[Zilong Huang]], [[Xinggang Wang]], [[Yunchao Wei]], [[Lichao Huang]], [[Humphrey S ......

Dual Attention Network for Scene Segmentation:双线并行的注意力

Dual Attention Network for Scene Segmentation * Authors: [[Jun Fu]], [[Jing Liu]], [[Haijie Tian]], [[Yong Li]], [[Yongjun Bao]], [[Zhiwei Fang]], [[H ......

Fully convolutional networks for semantic segmentation

Fully convolutional networks for semantic segmentation * Authors: [[Jonathan Long]], [[Evan Shelhamer]], [[Trevor Darrell]] DOI: 10.1109/CVPR.2015.729 ......

U-Net: Convolutional Networks for Biomedical Image Segmentation

U-Net: Convolutional Networks for Biomedical Image Segmentation * Authors: [[Olaf Ronneberger]], [[Philipp Fischer]], [[Thomas Brox]] Local library 初读 ......

SeaFormer: Squeeze-enhanced Axial Transformer for Mobile Semantic Segmentation

SeaFormer: Squeeze-enhanced Axial Transformer for Mobile Semantic Segmentation * Authors: [[Qiang Wan]], [[Zilong Huang]], [[Jiachen Lu]], [[Gang Yu]] ......

RefineNet: Multi-path Refinement Networks for High-Resolution Semantic Segmentation

RefineNet: Multi-path Refinement Networks for High-Resolution Semantic Segmentation * Authors: [[Guosheng Lin]], [[Anton Milan]], [[Chunhua Shen]], [[ ......

Expectation-Maximization Attention Networks for Semantic Segmentation 使用了EM算法的注意力

Expectation-Maximization Attention Networks for Semantic Segmentation * Authors: [[Xia Li]], [[Zhisheng Zhong]], [[Jianlong Wu]], [[Yibo Yang]], [[Zho ......

UNetFormer: A UNet-like transformer for efficient semantic segmentation of remote sensing urban scene imagery

UNetFormer: A UNet-like transformer for efficient semantic segmentation of remote sensing urban scene imagery * Authors: [[Libo Wang]], [[Rui Li]], [[ ......

SegViT: Semantic Segmentation with Plain Vision Transformers

SegViT: Semantic Segmentation with Plain Vision Transformers * Authors: [[Bowen Zhang]], [[Zhi Tian]], [[Quan Tang]], [[Xiangxiang Chu]], [[Xiaolin We ......

Context Prior for Scene Segmentation带上下文先验的分割

Context Prior for Scene Segmentation * Authors: [[Changqian Yu]], [[Jingbo Wang]], [[Changxin Gao]], [[Gang Yu]], [[Chunhua Shen]], [[Nong Sang]] DOI: ......
先验 下文 Segmentation Context Prior

UNet++: A Nested U-Net Architecture for Medical Image Segmentation

UNet++: A Nested U-Net Architecture for Medical Image Segmentation * Authors: [[Zongwei Zhou]], [[Md Mahfuzur Rahman Siddiquee]], [[Nima Tajbakhsh]], ......

Asymmetric Non-Local Neural Networks for Semantic Segmentation 非对称注意力

Asymmetric Non-Local Neural Networks for Semantic Segmentation * Authors: [[Zhen Zhu]], [[Mengdu Xu]], [[Song Bai]], [[Tengteng Huang]], [[Xiang Bai]] ......

PIDNet: A Real-time Semantic Segmentation Network Inspired by PID Controllers

PIDNet: A Real-time Semantic Segmentation Network Inspired by PID Controllers * Authors: [[Jiacong Xu]], [[Zixiang Xiong]], [[Shankar P. Bhattacharyya ......

Object Tracking Network Based on Deformable Attention Mechanism

Object Tracking Network Based on Deformable Attention Mechanism Local library 初读印象 comment:: (DeTrack)采用基于可变形注意力机制的编码器模块和基于自注意力机制的编码器模块相结合的方式进行特征交互。基于 ......

A Deformable Attention Network for High-Resolution Remote Sensing Images Semantic Segmentation可变形注意力

A Deformable Attention Network for High-Resolution Remote Sensing Images Semantic Segmentation * Authors: [[Renxiang Zuo]], [[Guangyun Zhang]], [[Rong ......

2021-CVPR-Transformer Tracking

Transformer Tracking 相关性在跟踪领域起着关键作用,特别是在最近流行的暹罗跟踪器中。相关操作是考虑模板与搜索区域之间相似性的一种简单的融合方式。然而,相关操作本身是一个局部线性匹配过程,导致语义信息的丢失并容易陷入局部最优,这可能是设计高精度跟踪算法的瓶颈。还有比相关性更好的特征 ......

Fully Attentional Network for Semantic Segmentation:FLANet

Fully Attentional Network for Semantic Segmentation * Authors: [[Qi Song]], [[Jie Li]], [[Chenghong Li]], [[Hao Guo]], [[Rui Huang]] 初读印象 comment:: (F ......

Segmentation Transformer: Object-Contextual Representations for Semantic Segmentation;OCRNet

Segmentation Transformer: Object-Contextual Representations for Semantic Segmentation * Authors: [[Yuhui Yuan]], [[Xiaokang Chen]], [[Xilin Chen]], [[ ......

【Linux】调试常见的应用程序奔溃“Segmentation fault (core dumped)”

https://blog.csdn.net/hello_nofail/article/details/129994481?ops_request_misc=%257B%2522request%255Fid%2522%253A%2522170264661316800227454508%2522%252 ......
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