leochangzliao / object-detection

Awesome Papers for Object Detection

Object-Detection

refer https://github.com/Sophia-11/Awesome-CV-Paper-Review/blob/master/README.md

arxiv19

Cascade RetinaNet:Maintaining Consistency for Single-StageObject Detection
https://arxiv.org/pdf/1907.06881v1.pdf

EfficientDet: Scalable and Efficient Object Detection
https://arxiv.org/abs/1911.09070
FreeAnchor: Learning to Match Anchors for VisualObject Detection
https://arxiv.org/pdf/1909.02466.pdf
FCOS: Fully Convolutional One-Stage Object Detection
https://arxiv.org/pdf/1904.01355.pdf　　

High-Resolution Representations for Labeling Pixels and Regions
https://arxiv.org/pdf/1904.04514.pdf　　

Bag of Freebies for Training Object Detection Neural Networks
https://arxiv.org/pdf/1902.04103.pdf

CVPR 2019

Generalized Intersection over Union: A Metric and A Loss for Bounding Box Regression https://arxiv.org/pdf/1902.09630.pdf

Feature Selective Anchor-Free Module for Single-Shot Object Detection
https://128.84.21.199/pdf/1903.00621.pdf

Bounding Box Regression with Uncertainty for Accurate Object Detection
https://github.com/yihui-he/KL-Loss

Augmentation for small object detection
https://arxiv.org/pdf/1902.07296.pdf

Region Proposal by Guided Anchoring
https://arxiv.org/pdf/1901.03278.pdf

Libra R-CNN: Towards Balanced Learning for Object Detection
https://arxiv.org/pdf/1904.02701.pdf

AAAI 2019

Object Detection based on Region Decomposition and Assembly https://arxiv.org/pdf/1901.08225v1.pdf

M2Det: A Single-Shot Object Detector based on Multi-Level Feature Pyramid Network https://arxiv.org/pdf/1811.04533.pdf

CVPR 2018

Focal Loss for Dense Object Detection https://arxiv.org/pdf/1708.02002.pdf
Cascade R-CNN: Delving into High Quality Object Detection
http://openaccess.thecvf.com/content_cvpr_2018/papers/Cai_Cascade_R-CNN_Delving_CVPR_2018_paper.pdf

ECCV 2018

Parallel Feature Pyramid Network for Object Detection http://openaccess.thecvf.com/content_ECCV_2018/papers/Seung-Wook_Kim_Parallel_Feature_Pyramid_ECCV_2018_paper.pdf
Receptive Field Block Net for Accurate and Fast Object Detection
http://openaccess.thecvf.com/content_ECCV_2018/papers/Songtao_Liu_Receptive_Field_Block_ECCV_2018_paper.pdf
Revisiting RCNN: On Awakening the Classification Power of Faster RCNN https://arxiv.org/pdf/1803.06799.pdf

NIPS 2018

SNIPER: Efficient Multi-Scale Training http://papers.nips.cc/paper/8143-sniper-efficient-multi-scale-training.pdf

arXiv' 18

YOLOv3: An Incremental Improvement https://pjreddie.com/media/files/papers/YOLOv3.pdf

CVPR 2017

YOLO9000: Better, Faster, Stronger https://arxiv.org/pdf/1901.08225.pdf

Feature Pyramid Networks for Object Detection http://openaccess.thecvf.com/content_cvpr_2017/papers/Lin_Feature_Pyramid_Networks_CVPR_2017_paper.pdf

ICCV 2017

Focal Loss for Dense Object Detection https://arxiv.org/pdf/1708.02002.pdf
Mask R-CNN http://openaccess.thecvf.com/content_ICCV_2017/papers/He_Mask_R-CNN_ICCV_2017_paper.pdf

CVPR 2016

You Only Look Once: Unified, Real-Time Object Detection https://arxiv.org/pdf/1506.02640.pdf

Training Region-based Object Detectors with Online Hard Example Mining https://arxiv.org/pdf/1604.03540.pdf

SSD: Single Shot MultiBox Detector https://arxiv.org/pdf/1512.02325.pdf

NIPS 2016

R-FCN: Object Detection via Region-based Fully Convolutional Networks https://arxiv.org/pdf/1605.06409.pdf

NIPS 2015

Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks https://papers.nips.cc/paper/5638-faster-r-cnn-towards-real-time-object-detection-with-region-proposal-networks.pdf

CVPR 2015

Fast R-CNN https://arxiv.org/pdf/1504.08083.pdf