CVPR2019 | 29篇目标检测相关论文汇总(部分含源码)

栏目: 编程工具 · 发布时间: 6年前

内容简介:计算机视觉顶级会议CVPR2019 accepted list已经公布,极市已将目前收集到的公开论文总结到github上(目前已收集546篇),后续会不断更新,欢迎关注,也欢迎大家提交自己的论文:https://github.com/extreme-assistant/cvpr2019

极市正在推出 CVPR2019的专题直播分享会 邀请CVPR2019的论文作者进行线上直播, 分享优秀的科研工作和技术干货,也欢迎各位小伙伴自荐或推荐优秀的CVPR论文作者到极市进行技术分享~

本周四(5月9日)晚, 中科院自动化所模式识别国家重点实验室的张志鹏 ,将为我们分享

基于siamese网络的单目标跟踪 (CVPR2019 Oral) ,公众号回复 “41” 即可获取直播详情。

计算机视觉顶级会议CVPR2019 accepted list已经公布,极市已将目前收集到的公开论文总结到github上(目前已收集546篇),后续会不断更新,欢迎关注,也欢迎大家提交自己的论文:

https://github.com/extreme-assistant/cvpr2019

今天为大家分享 CVPR2019  目标检测 相关论文的汇总,本文首发于极市平台知乎专栏

https://zhuanlan.zhihu.com/p/60823819 ,欢迎 关注专栏获取本系列后续更新 ~如有遗漏也欢迎大家留言补充或提出建议。

ps.极市也曾分享过一篇: CVPR2019目标检测方法进展综述 ,可以结合本文一起阅读~

1、Stereo R-CNN based 3D Object Detection for Autonomous Driving

作者:Peiliang Li, Xiaozhi Chen, Shaojie Shen

论文链接:https://arxiv.org/abs/1902.09738

CVPR2019 | 29篇目标检测相关论文汇总(部分含源码)

2、Generalized Intersection over Union: A Metric and A Loss for Bounding Box Regression

作者:Hamid Rezatofighi, Nathan Tsoi, JunYoung Gwak, Amir Sadeghian, Ian Reid, Silvio Savarese

论文解读: CVPR2019 | 目标检测新文:Generalized Intersection over Union

3、ROI-10D: Monocular Lifting of 2D Detection to 6D Pose and Metric Shape 

作者:Fabian Manhardt, Wadim Kehl, Adrien Gaidon

4、Bi-Directional Cascade Network for Perceptual Edge Detection

作者:Jianzhong He, Shiliang Zhang, Ming Yang, Yanhu Shan, Tiejun Huang

Github源码:

https://github.com/pkuCactus/BDCN

5、RepMet: Representative-based metric learning for classification and one-shot object detection

作者:Leonid Karlinsky, Joseph Shtok, Sivan Harary, Eli Schwartz, Amit Aides, Rogerio Feris, Raja Giryes, Alex M. Bronstein

论文链接:https://arxiv.org/abs/1806.04728

CVPR2019 | 29篇目标检测相关论文汇总(部分含源码)

6、Region Proposal by Guided Anchoring

作者:Jiaqi Wang, Kai Chen, Shuo Yang, Chen Change Loy, Dahua Lin

论文解读: Guided Anchoring: 物体检测器也能自己学 Anchor

Github链接:https://github.com/open-mmlab/mmdetection

CVPR2019 | 29篇目标检测相关论文汇总(部分含源码)

7、Less is More: Learning Highlight Detection from Video Duration

作者:Bo Xiong, Yannis Kalantidis, Deepti Ghadiyaram, Kristen Grauman

8、AIRD: Adversarial Learning Framework for Image Repurposing Detection

作者:Ayush Jaiswal, Yue Wu, Wael AbdAlmageed, Iacopo Masi, Premkumar Natarajan

9、Feature Selective Anchor-Free Module for Single-Shot Object Detection

作者:Chenchen Zhu, Yihui He, Marios Savvides

论文解读: CVPR2019 | FSAF:来自CMU的Single-Shot目标检测算法

一作直播: CVPR2019 专题直播 | CMU 诸宸辰:基于 Anchor-free 特征选择模块的单阶目标检测

CVPR2019 | 29篇目标检测相关论文汇总(部分含源码)

10、Learning Attraction Field Representation for Robust Line Segment Detection

作者:Nan Xue, Song Bai, Fudong Wang, Gui-Song Xia, Tianfu Wu, Liangpei Zhang

代码链接:

https://github.com/cherubicXN/afm_cvpr2019

11、Latent Space Autoregression for Novelty Detection

作者:Davide Abati, Angelo Porrello, Simone Calderara, Rita Cucchiara

代码链接: https://github.com/aimagelab/novelty-detection

12、Strong-Weak Distribution Alignment for Adaptive Object Detection

作者:Kuniaki Saito, Yoshitaka Ushiku, Tatsuya Harada, Kate Saenko

13、Few-shot Adaptive Faster R-CNN

作者:Tao Wang, Xiaopeng Zhang, Li Yuan, Jiashi Feng

14、Attention Based Glaucoma Detection: A Large-scale Database and CNN Mode l

作者:Liu Li, Mai Xu, Xiaofei Wang, Lai Jiang, Hanruo Liu

论文链接:https://arxiv.org/abs/1903.10831

CVPR2019 | 29篇目标检测相关论文汇总(部分含源码)

15、Bounding Box Regression with Uncertainty for Accurate Object Detection(目标检测边界框回归损失算法)

作者:Yihui He, Chenchen Zhu, Jianren Wang, Marios Savvides, Xiangyu Zhang

代码链接:https://github.com/yihui-he/KL-Loss

CVPR2019 | 29篇目标检测相关论文汇总(部分含源码)

16、Precise Detection in Densely Packed Scenes

作者:Eran Goldman , Roei Herzig, Aviv Eisenschtat, Jacob Goldberger, Tal Hassner

17、Activity Driven Weakly Supervised Object Detection

作者:Zhenheng Yang, Dhruv Mahajan, Deepti Ghadiyaram, Ram Nevatia, Vignesh Ramanathan

18、Monocular 3D Object Detection Leveraging Accurate Proposals and Shape Reconstruction

作者:Jason Ku, Alex D. Pon, Steven L. Waslander

19、Libra R-CNN: Towards Balanced Learning for Object Detection

作者:Jiangmiao Pang, Kai Chen, Jianping Shi, Huajun Feng, Wanli Ouyang, Dahua Lin

论文链接:https://arxiv.org/abs/1904.02701

CVPR2019 | 29篇目标检测相关论文汇总(部分含源码)

20、Moving Object Detection under Discontinuous Change in Illumination Using Tensor Low-Rank and Invariant Sparse Decomposition

作者:Moein Shakeri, Hong Zhang

21、Towards Universal Object Detection by Domain Attention

作者:Xudong Wang, Zhaowei Cai, Dashan Gao, Nuno Vasconcelos

项目链接:

http://www.svcl.ucsd.edu/projects/universal-detection/

22、NAS-FPN: Learning Scalable Feature Pyramid Architecture for Object Detection

作者:Golnaz Ghiasi, Tsung-Yi Lin, Ruoming Pang, Quoc V. Le

23、Deep Anomaly Detection for Generalized Face Anti-Spoofing

作者:Daniel Pérez-Cabo, David Jiménez-Cabello, Artur Costa-Pazo, Roberto J. López-Sastre

24、Cascaded Partial Decoder for Fast and Accurate Salient Object Detection

作者:Zhe Wu, Li Su, Qingming Huang

论文链接:https://arxiv.org/abs/1904.08739

25、A Simple Pooling-Based Design for Real-Time Salient Object Detection

作者:Jiang-Jiang Liu, Qibin Hou, Ming-Ming Cheng, Jiashi Feng, Jianmin Jiang

源码链接:http://mmcheng.net/poolnet/

CVPR2019 | 29篇目标检测相关论文汇总(部分含源码)

26、CapSal: Leveraging Captioning to Boost Semantics for Salient Object Detection

作者:Lu Zhang; Huchuan Lu ; Zhe Lin ; Jianming Zhang; You He

论文链接:https://drive.google.com/open?id=1JcZMHBXEX-7AR1P010OXg_wCCC5HukeZ (需要申请)

27、Deep Fitting Degree Scoring Network for Monocular 3D Object Detection

作者:Lijie Liu1, Jiwen Lu, Chunjing Xu, Qi Tian, Jie Zhou

28、A Mutual Learning Method for Salient Object Detection with intertwined Multi-Supervision

作者:Runmin Wu, Mengyang Feng, Wenlong Guan, Dong Wang, Huchuan Lu, Errui Ding

论文链接:待定

源码链接:

https://github.com/JosephineRabbit/MLMSNet

29、ScratchDet:Exploring to Train Single-Shot Object Detectors from Scratch(Oral)

作者:Rui Zhu, Shifeng Zhang, Xiaobo Wang, Longyin Wen, Hailin Shi, Liefeng Bo, Tao Mei

源码链接:

https://github.com/KimSoybean/ScratchDet

论文解读: CVPR 2019 Oral | 京东AI研究院提出 ScratchDet:随机初始化训练SSD目标检测器

CVPR2019 | 29篇目标检测相关论文汇总(部分含源码)

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CVPR2019 | 29篇目标检测相关论文汇总(部分含源码)

觉得有用麻烦给个好看啦~    CVPR2019 | 29篇目标检测相关论文汇总(部分含源码)


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