记录自己比较感兴趣的2D目标检测文章
| Date | Pub. | Title | Code |
|---|---|---|---|
| 2022 | ECCV | ObjectBox: From Centers to Boxes for Anchor-Free Object Detection | https://github.com/mohsenzand/objectbox |
| 2021 | MM | Disentangle Your Dense Object Detector | https://github.com/zehuichen123/DDOD |
| 2021 | CVPR | VarifocalNet: An IoU-aware Dense Object Detector | https://github.com/hyz-xmaster/VarifocalNet |
| 2021 | CVPR | Sparse R-CNN: End-to-End Object Detection with Learnable Proposals | https://github.com/PeizeSun/SparseR-CNN |
| 2020 | ECCV | Dynamic R-CNN: Towards High Quality Object Detection via Dynamic Training | https://github.com/hkzhang95/DynamicRCNN |
| 2020 | ECCV | Side-Aware Boundary Localization for More Precise Object Detection | https://github.com/open-mmlab/mmdetection |
| 2020 | CVPR | CentripetalNet: Pursuing High-quality Keypoint Pairs for Object Detection | https://github.com/KiveeDong/CentripetalNet |
| 2020 | CVPR | NAS-FCOS: Fast Neural Architecture Search for Object Detection | https://github.com/open-mmlab/mmdetection |
| 2020 | TIP | FoveaBox: Beyond Anchor-based Object Detector | https://github.com/taokong/FoveaBox |
| 2020 | NIPS | RepPoints V2: Verification Meets Regression for Object Detection | https://github.com/Scalsol/RepPointsV2 |
| 2019 | ICCV | RepPoints: Point Set Representation for Object Detection | https://github.com/microsoft/RepPoints |
| 2019 | NIPS | Cascade RPN: Delving into High-Quality Region Proposal Network with Adaptive Convolution | https://github.com/thangvubk/Cascade-RPN |
| 2019 | ICCV | FCOS: Fully Convolutional One-Stage Object Detection | https://github.com/tianzhi0549/FCOS |
| 2019 | ICCV | Scale-Aware Trident Networks for Object Detection | https://github.com/open-mmlab/mmdetection |
| 2019 | CVPR | Libra R-CNN: Towards Balanced Learning for Object Detection | https://github.com/open-mmlab/mmdetection |
| 2019 | CVPR | Objects as Points | https://github.com/xingyizhou/CenterNet |
| 2019 | CVPR | Region Proposal by Guided Anchoring | https://github.com/open-mmlab/mmdetection |
| 2019 | CVPR | Grid R-CNN | https://github.com/open-mmlab/mmdetection |
| 2018 | ECCV | CornerNet: Detecting Objects as Paired Keypoints | https://github.com/princeton-vl/CornerNet |
| 2018 | CVPR | Cascade R-CNN: High Quality Object Detection and Instance Segmentation | https://github.com/zhaoweicai/cascade-rcnn |
| 2017 | ICCV | Focal Loss for Dense Object Detection | https://github.com/open-mmlab/mmdetection |
| 2016 | ECCV | SSD: Single Shot MultiBox Detector | https://github.com/weiliu89/caffe |
| 2015 | NIPS | Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks | https://github.com/ShaoqingRen/faster_rcnn |
| 2015 | ICCV | Fast R-CNN | https://github.com/rbgirshick/fast-rcnn |
| Date | Pub. | Title | Code |
|---|---|---|---|
| 2023 | — | YOLOV8 | https://github.com/ultralytics/ultralytics |
| 2022 | — | DAMO-YOLO | https://github.com/tinyvision/DAMO-YOLO |
| 2022 | arXiv | YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors | https://github.com/wongkinyiu/yolov7 |
| 2022 | — | Yolov6 | https://github.com/meituan/YOLOv6 |
| 2022 | arXiv | PP-YOLOE: An evolved version of YOLO | https://github.com/PaddlePaddle/PaddleDetection |
| 2021 | Tech Report | YOLOX: Exceeding YOLO Series in 2021 | https://github.com/Megvii-BaseDetection/YOLOX |
| 2021 | aiXiv | You Only Learn One Representation: Unified Network for Multiple Tasks | https://github.com/WongKinYiu/yolor |
| 2021 | CVPR | Scaled-YOLOv4: Scaling Cross Stage Partial Network | https://github.com/WongKinYiu/ScaledYOLOv4 |
| 2021 | arXiv | PP-YOLOv2: A Practical Object Detector | https://github.com/PaddlePaddle/PaddleDetection |
| 2020 | arXiv | PP-YOLO: An Effective and Efficient Implementation of Object Detector | https://github.com/PaddlePaddle/PaddleDetection |
| 2020 | — | Yolov5 | https://github.com/ultralytics/yolov5 |
| 2020 | arXiv | Yolov4: Optimal speed and accuracy of object detection | https://github.com/AlexeyAB/darknet |
| 2018 | Tech Report | YOLOv3: An Incremental Improvement | — |
| 2017 | CVPR | YOLO9000: Better, Faster, Stronger | — |
| 2016 | CVPR | You Only Look Once: Unified, Real-Time Object Detection | — |
| Date | Pub. | Title | Code |
|---|---|---|---|
| 2021 | ICCV | TOOD: Task-aligned One-stage Object Detection | https://github.com/fcjian/TOOD |
| 2021 | ICCV | Reconcile Prediction Consistency for Balanced Object Detection | — |
| 2021 | ICCV | Mutual Supervision for Dense Object Detection | |
| 2020 | CVPR | Rethinking Classification and Localization for Object Detection | https://github.com/wuyuebupt/doubleheadsrcnn |
| 2020 | CVPR | Multiple Anchor Learning for Visual Object Detection | https://github.com/KevinKecc/MAL |
| Date | Pub. | Title | Code |
|---|---|---|---|
| 2023 | arXiv | RT-DETR: DETRs Beat Yolos on Real-time Object Detection | https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/rtdetr#%E6%A8%A1%E5%9E%8B |
| 2022 | CVPR | DN-DETR: Accelerate DETR Training by Introducing Query DeNoising | https://github.com/fengli-ust/dn-detr |
| 2021 | ICLR | Deformable DETR: Deformable Transformers for End-to-End Object Detection | https://github.com/fundamentalvision/Deformable-DETR |
| 2021 | ICCV | Rethinking Transformer-based Set Prediction for Object Detection | https://github.com/edward-sun/tsp-detection |
| 2021 | ICCV | Dynamic DETR: End-to-End Object Detection with Dynamic Attention | — |
| 2020 | ECCV | End-to-End Object Detection with Transformers | https://github.com/facebookresearch/detr |
| Date | Pub. | Title | Code |
|---|---|---|---|
| 2022 | CVPR | Localization Distillation for Dense Object Detection | https://github.com/HikariTJU/LD |
| 2022 | CVPR | Focal and Global Knowledge Distillation for Detectors | https://github.com/yzd-v/FGD |
| 2022 | WACV | Improving Object Detection by Label Assignment Distillation | https://github.com/cybercore-co-ltd/CoLAD |
| 2021 | CVPR | Distilling Object Detectors via Decoupled Features | https://github.com/ggjy/DeFeat.pytorch |
| 2021 | CVPR | General Instance Distillation for Object Detection | — |
| Date | Pub. | Title | Code |
|---|---|---|---|
| 2022 | ECCV | You Should Look at All Objects | https://github.com/charlespikachu/yslao |
| 2021 | CVPR | You Only Look One-level Feature | https://github.com/megvii-model/YOLOF |
| 2019 | CVPR | Feature Selective Anchor-Free Module for Single-Shot Object Detection | https://github.com/open-mmlab/mmdetection |
| Date | Pub. | Title | Code |
|---|---|---|---|
| 2023 | arXiv | TinyDet: Accurate Small Object Detection in Lightweight Generic Detectors | https://github.com/hustvl/TinyDet |
| 2022 | ECCV | RFLA: Gaussian Receptive Field based Label Assignment for Tiny Object Detection | https://github.com/chasel-tsui/mmdet-rfla |
| 2022 | CVPR | QueryDet: Cascaded Sparse Query for Accelerating High-Resolution Small Object Detection | https://github.com/ChenhongyiYang/QueryDet-PyTorch |
| 2020 | TSMC | A Survey of the Four Pillars for Small Object Detection: Multiscale Representation, Contextual Information, Super-Resolution, and Region Proposal |
| Date | Pub. | Title | Code |
|---|---|---|---|
| 2021 | CVPR | Scale-aware Automatic Augmentation for Object Detection | https://github.com/dvlab-research/SA-AutoAug |
| Date | Pub. | Title | Code |
|---|---|---|---|
| 2021 | CVPR | Towards Open World Object Detection | https://github.com/JosephKJ/OWOD |
| Date | Pub. | Title | Code |
|---|---|---|---|
| 2021 | ICCV | Exploring Classification Equilibrium in Long-Tailed Object Detection | https://github.com/fcjian/loce |
| 2021 | ICCV | MOSAICOS: A Simple and Effective Use of Object-Centric Images for Long-Tailed Object Detection | https://github.com/czhang0528/MosaicOS |
| Date | Pub. | Title | Code |
|---|---|---|---|
| 2022 | ECCV | Point-to-Box Network for Accurate Object Detection via Single Point Supervision | https://github.com/ucas-vg/P2BNet |
| Date | Pub. | Title | Code |
|---|---|---|---|
| 2022 | CVPR | Target-aware Dual Adversarial Learning and a Multi-scenario Multi-Modality Benchmark to Fuse Infrared and Visible for Object Detection | https://github.com/JinyuanLiu-CV/TarDAL |
| 2022 | ECCV | Multimodal Object Detection via Probabilistic Ensembling | https://github.com/Jamie725/RGBT-detection |
| Date | Pub. | Title | Code |
|---|---|---|---|
| 2022 | arXiv | Understanding CNN Fragility When Learning With Imbalanced Data | — |
| 2022 | arXiv | TSAA: A Two-Stage Anchor Assignment Method towards Anchor Drift in Crowded Object Detection | — |
| 2019 | arXiv | Empirical Upper Bound in Object Detection and More | — |
| Date | Pub. | Title | Code |
|---|---|---|---|
| 2022 | arXiv | DiffusionDet: Diffusion Model for Object Detection | https://github.com/shoufachen/diffusiondet |
| Date | Pub. | Title | Code |
|---|---|---|---|
| 2021 | arXiv | Focal and Efficient IOU Loss for Accurate Bounding Box Regression | |
| 2021 | arXiv | Alpha-IoU: A Family of Power Intersection over Union Losses for Bounding Box Regression | https://github.com/jacobi93/alpha-iou |
| 2020 | AAAI | Distance-IoU Loss: Faster and Better Learning for Bounding Box Regression | https://github.com/Zzh-tju/DIoU |
| 2019 | CVPR | Generalized Intersection over Union: A Metric and A Loss for Bounding Box Regression | - |
文章浏览阅读1.5k次。原文地址https://blog.csdn.net/kiddd_fu/article/details/78247290终极解决方案出现(non-fast-forward)的根本原因是repository已经存在项目且不是你本人提交（我知道是大概率你提交的，但是git只认地址），你commit的项目和远程repo不一样。这时该怎么办呢？很简单，把远端项目拉回本地：git pull然而pu..._同类项目合并方案
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文章浏览阅读1.2k次，点赞13次，收藏9次。主流的开发语言和开发环境介绍 _开发语言
文章浏览阅读595次。作为一个WPF程序员，我最希望看到的是WPF的应用，或者更确切的说是绚丽的应用，虽然限于自身的实力还不能拿出成绩来，但看到别人的作品时，心里还是有很大的宽慰——WPF是可以做出更加动人地产品的，只要你坚定的走下去，带着不满现状的追求走下去。 下图是Telerik的WPF控件，我相信很多人也下过他的DEMO，研究过他的代码，并由此激起对WPF的信心。今天我们就来仿造他的Drag..._wpf 自定义控件示例
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文章浏览阅读955次。周计划和学习总结
文章浏览阅读172次。Windows环境中同时安装Oracle9i 和10g 原创者：大胖黑马（授权发布）简单说一下在windows的同一用户下，安装Oracle的9i、10g 的方法1、安装版本需要从低到高。也就是说先安装9i的数据库，然后安装10g的数据库2、安装目录分开。3、在低版本的数据库安装完成后，最好通过..._oracle 9i 和oracle 10g同时使用
文章浏览阅读305次。使用SVM进行手写数据OCR在 kNN 中我们直接使用像素的灰度值作为特征向量。这次我们要使用方向梯度直方图Histogram of Oriented Gradients （HOG）作为特征向量。在计算 HOG 前我们使用图片的二阶矩对其进行抗扭斜（deskew）处理，也就是把歪了的图片摆正。所以我们首先要定义一个函数 deskew()，它可以对一个图像进行抗扭斜处理。下面就是 deskew() 函数：..._python opencv 计算向量
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文章浏览阅读2.1k次，点赞3次，收藏13次。最近做SFTP连接获取文件，遇到好多坑，记录一下防止以后重复踩坑无效秘钥文件1.版本低导致文件无效2.windows系统不支持ppk秘钥文件，必须转换成pem秘钥文件com.jcraft.jsch.JSchException: invalid privatekey: C:/upload/tpl/privateKey.ppk at com.jcraft.jsch.IdentityFile.<init>(IdentityFile.java:302) at com.jc..._如何用sftp密钥下载文件到本地密钥
这篇文章介绍了通过在阿里云镜像网站下载epel源来安装nginx的过程，包括下载epel源、安装nginx rpm包、访问nginx默认网页以及nginx的安装配置文件路径和默认文件位置。
文章浏览阅读9.2k次。oracle expdp/impdp 数据泵导入导出# 创建directory，指定导入导出时的数据存储路径create directory dir_dp as 'd:/database/dir_dp';# 授权grant read,write on directory dir_dp to user_name;# 查看目录及权限select * from dba_directories;-_impdb schemas