CVPR2022目标检测方向论文

完整的paper list已经放出来了，可以直接查看。

https://cvpr2022.thecvf.com/sites/default/files/2022-04/accepted%20papers.xlsx

[1] SIGMA: Semantic-complete Graph Matching for Domain Adaptive Object Detection

paper: https://arxiv.org/pdf/2203.06398

code: https://github.com/CityU-AIM-Group/SIGMA

[2] Democracy Does Matter: Comprehensive Feature Mining for Co-Salient Object Detection

paper: https://arxiv.org/pdf/2203.05787

code: TBD

[3] Canonical Voting: Towards Robust Oriented Bounding Box Detection in 3D Scenes

paper: https://arxiv.org/pdf/2011.12001

code: https://github.com/qq456cvb/CanonicalVoting

[4] Back to Reality: Weakly-supervised 3D Object Detection with Shape-guided Label Enhancement

paper: https://arxiv.org/pdf/2203.05238

code: https://github.com/xuxw98/BackToReality

[5] Unknown-Aware Object Detection: Learning What You Don't Know from Videos in the Wild

paper: https://arxiv.org/pdf/2203.03800

code: https://github.com/deeplearning-wisc/stud

[6] Zoom In and Out: A Mixed-scale Triplet Network for Camouflaged Object Detection

paper: https://arxiv.org/pdf/2203.02688

code: https://github.com/lartpang/ZoomNet

[7] DN-DETR: Accelerate DETR Training by Introducing Query DeNoising

paper: https://arxiv.org/pdf/2203.01305

code: https://github.com/FengLi-ust/DN-DETR

[8] Localization Distillation for Dense Object Detection

paper: https://arxiv.org/pdf/2102.12252

code: GitHub - HikariTJU/LD: Localization Distillation for Dense Object Detection (CVPR 2022)

[9] Accelerating DETR Convergence via Semantic-Aligned Matching

paper: https://arxiv.org/pdf/2203.06883

code: GitHub - ZhangGongjie/SAM-DETR: Official PyTorch Implementation of SAM-DETR (CVPR 2022)

[10] Point Density-Aware Voxels for LiDAR 3D Object Detection

paper: https://arxiv.org/pdf/2203.05662

code: https://github.com/TRAILab/PDV

[11] Spatial Commonsense Graph for Object Localisation in Partial Scenes

paper: https://arxiv.org/pdf/2203.05380

code: Spatial Commonsense Graph for Object Localisation in Partial Scenes

[12] Adversarial Texture for Fooling Person Detectors in the Physical World

paper: https://arxiv.org/pdf/2203.03373

code: TBD

[13] Rethinking Efficient Lane Detection via Curve Modeling

paper: https://arxiv.org/pdf/2203.02431

code: GitHub - voldemortX/pytorch-auto-drive: Segmentation models (ERFNet, ENet, DeepLab, FCN...) and Lane detection models (SCNN, PRNet, RESA, LSTR, BézierLaneNet...) based on PyTorch with mixed precision training

[14] A Versatile Multi-View Framework for LiDAR-based 3D Object Detection with Guidance from Panoptic Segmentation

paper: https://arxiv.org/pdf/2203.02133

code: TBD

[15] Pseudo-Stereo for Monocular 3D Object Detection in Autonomous Driving

paper: https://arxiv.org/pdf/2203.02112

code: GitHub - revisitq/Pseudo-Stereo-3D

[16] Weakly Supervised Object Localization as Domain Adaption

paper: https://arxiv.org/pdf/2203.01714

code: https://github.com/zh460045050/DA-WSOL_CVPR2022

[17] Focal and Global Knowledge Distillation for Detectors

paper: https://arxiv.org/pdf/2111.11837

code: GitHub - yzd-v/FGD: Focal and Global Knowledge Distillation for Detectors (CVPR 2022)

CVPR2022目标检测方向论文相关推荐

【CVPR2020】目标检测方向论文更新
关注上方"深度学习技术前沿",选择"星标公众号", 资源干货,第一时间送达! [1] Learning Human-Object Interaction Det ...
CVPR2022 目标检测方向文章（附摘要）
目录一.2D目标检测 [1] SIGMA: Semantic-complete Graph Matching for Domain Adaptive Object Detection(SIGMA:域 ...
CVPR2020目标检测方向论文
CVPR 2020的paper list已经放出来了,链接如下: http://cvpr2020.thecvf.com/program/main-conference CVPR 2020的录用结果已经 ...
CVPR2021目标检测方向论文
完整的paper list已经出来了. http://cvpr2021.thecvf.com/node/142 CVPR2021录取结果刚出来,不过离全部的paper list还有一段时间,接下来应该 ...
CVPR2022目标检测文章汇总+创新点简要分析
大概总结了一下CVPR2022目标检测领域的文章,并未包括跨域和3D目标检测. 个人总结,难免有疏漏,大家参考一下就好. CVPR 2022 一.常规目标检测 1. MViTv2: Improved ...
对象检测目标小用什么模型好_[目标检测] YOLO4论文中文版
点击上方蓝字关注我呀! [目标检测] YOLO4论文中文版文章目录 YOLO4论文中文版摘要 1.介绍 2.相关工作 2.1.目标检测模型 2.2.Bag of freebies 2.3.Ba ...
【R-CNN论文翻译】目标检测经典论文R-CNN最新版本（v5版）全面中文翻译
R-CNN目标检测的奠基性文章,学习目标检测必看的经典论文之一,后续有Fast R-CNN,Faster R-CNN一系列论文. 目前网上能找到的论文翻译版本要么不全,要么不是最新版本的(论文从201 ...
单阶段目标检测重要论文总结
文章目录一.Yolov1 1.论文简介 2.检测原理 3.结构设计 4.疑难问题 5.论文总结二.Yolov2 1.论文简介 2.更好.更快.更强 1)为什么更好? 2)为什么更快? 3)为什么更 ...
目标检测经典论文——YOLOv2论文翻译（纯中文版）：YOLO9000：更好、更快、更强
目标检测经典论文翻译汇总:[翻译汇总] 翻译pdf文件下载:[下载地址] 此版为纯中文版,中英文对照版请稳步:[YOLOv2中英文对照版] YOLO9000:更好.更快.更强 Joseph Redmo ...

CVPR2022目标检测方向论文

CVPR2022目标检测方向论文相关推荐

最新文章

热门文章