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的录用结果已经出来挺久了，不过估计还得过一段时间才能给出完整的接收列表。近期在关注目标检测相关的论文，因此收集一些今年CVPR最新的论文来看看，持续更新中。

 

[1] Bridging the Gap Between Anchor-based and Anchor-free Detection via Adaptive Training Sample Selection

paper: https://arxiv.org/abs/1912.02424 

code: https://github.com/sfzhang15/ATSS

 

[2] EfficientDet: Scalable and Efficient Object Detection

paper: https://arxiv.org/abs/1911.09070 

code: https://github.com/google/automl/tree/master/efficientdet

 

[3] Few-Shot Object Detection with Attention-RPN and Multi-Relation Detector

paper: https://arxiv.org/abs/1908.01998

code: TBD

dataset: https://github.com/fanq15/Few-Shot-Object-Detection-Dataset

 

[4] Hit-Detector: Hierarchical Trinity Architecture Search for Object Detection

paper: https://arxiv.org/abs/2003.11818

code: https://github.com/ggjy/HitDet.pytorch

 

[5] BiDet: An Efficient Binarized Object Detector

paper: https://arxiv.org/abs/2003.03961

code: https://github.com/ZiweiWangTHU/BiDet

 

[6] Harmonizing Transferability and Discriminability for Adapting Object Detectors

paper: https://arxiv.org/abs/2003.06297

code: https://github.com/chaoqichen/HTCN

 

[7] Noise-Aware Fully Webly Supervised Object Detection

paper: TBD

code: https://github.com/shenyunhang/NA-fWebSOD

 

[8] NAS-FCOS: fast neural architecture search for object detection

paper: https://arxiv.org/abs/1906.04423

code: TBD

 

[9] CentripetalNet: Pursuing High-quality Keypoint Pairs for Object Detection

paper: https://arxiv.org/abs/2003.09119

code: https://github.com/KiveeDong/CentripetalNet

 

[10] Cross-domain Object Detection through Coarse-to-Fine Feature Adaptation

paper: https://arxiv.org/abs/2003.10275

code: TBD

 

[11] Revisiting the Sibling Head in Object Detector

paper: https://arxiv.org/abs/2003.07540

code: https://github.com/Sense-X/TSD

 

[12] DR Loss: Improving Object Detection by Distributional Ranking

paper: https://arxiv.org/abs/1907.10156

code: https://github.com/idstcv/DR_loss

 

[13] Exploring Categorical Regularization for Domain Adaptive Object Detection

paper: https://arxiv.org/abs/2003.09152

code: https://github.com/Megvii-Nanjing/CR-DA-DET

 

[14] Detection in Crowded Scenes: One Proposal, Multiple Predictions

paper: https://arxiv.org/abs/2003.09163

code: https://github.com/megvii-model/CrowdDetection

 

[15] Camouflaged Object Detection

paper: http://mftp.mmcheng.net/Papers/20CVPR_Camouflag.pdf

code: TBD

 

[16] Scale-Equalizing Pyramid Convolution for Object Detection

paper: https://arxiv.org/abs/2005.03101

code: https://github.com/jshilong/SEPC

 

[17] Instance-aware, Context-focused, and Memory-efficient Weakly Supervised Object Detection

paper: https://arxiv.org/abs/2004.04725

code: https://github.com/NVlabs/wetectron

 

[18] Rethinking Classification and Localization for Object Detection

paper: https://arxiv.org/abs/1904.06493

code: TBD

 

[19] Dynamic Refinement Network for Oriented and Densely Packed Object Detection

paper: https://arxiv.org/abs/2005.09973

code: https://github.com/Anymake/DRN_CVPR2020