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https://github.com/DavidTai416/Object-Detection-Development#1-classical--papers
Rich feature hierarchies for accurate object detection and semantic segmentationhttps://arxiv.org/pdf/1311.2524
Spatial Pyramid Pooling in Deep Convolutional Networks for Visualhttps://arxiv.org/pdf/1406.4729
Cascaded Sparse Spatial Bins for Efficient and Effective Generic Object Detectionhttps://arxiv.org/pdf/1504.07029
Fast R-CNNhttps://arxiv.org/pdf/1504.08083
Towards Real-Time Object Detection with Region Proposal Networkshttps://arxiv.org/pdf/1506.01497
Object Detection via Region-based Fully Convolutional Networkshttps://arxiv.org/pdf/1605.06409
SSD: Single-Shot MultiBox Detectorhttps://arxiv.org/pdf/1512.02325
PVANET: Deep but Lightweight Neural Networks for Real-time Object Detectionhttps://arxiv.org/pdf/1608.08021v1.pdf
YOLO9000: better,faster,strongerhttps://arxiv.org/pdf/1612.08242
You Only Look Once-Unified, Real-Time Object Detectionhttps://arxiv.org/pdf/1506.02640
Speed_Accuracy trade-offs for modern convolutional object detectorshttps://arxiv.org/pdf/1611.10012
DSSD : Deconvolutional Single Shot Detectorhttps://arxiv.org/pdf/1701.06659.pdf
Deformable Convolutional Networkshttps://arxiv.org/pdf/1703.06211
Feature Pyramid Networks for Object Detectionhttps://arxiv.org/pdf/1612.03144.pdf
DSOD: Learning Deeply Supervised Object Detectors from Scratchhttps://arxiv.org/pdf/1708.01241
Focal Loss for Dense Object Detectionhttps://arxiv.org/pdf/1708.02002
Mask R-CNNhttps://arxiv.org/pdf/1703.06870
Light-Head R-CNN_In Defense of Two-Stage Object Detectorhttps://arxiv.org/pdf/1711.07264
https://github.com/DavidTai416/Object-Detection-Development#2datasetbenchmarks
https://github.com/DavidTai416/Object-Detection-Development#3great-open-code
MatCAFFEhttps://github.com/ShaoqingRen/faster_rcnn
PyCAFFEhttps://github.com/rbgirshick/py-faster-rcnn
Tensorflowhttps://github.com/smallcorgi/Faster-RCNN_TF
PyTorchhttps://github.com/longcw/faster_rcnn_pytorch
mx-Nethttps://github.com/precedenceguo/mx-rcnn
mx-Nethttps://github.com/msracver/Deformable-ConvNets
PyTorchhttps://github.com/oeway/pytorch-deform-conv
MatCAFFEhttps://github.com/daijifeng001/R-FCN
PyCAFFEhttps://github.com/daijifeng001/R-FCN
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CAFFE-MultiGPUhttps://github.com/bharatsingh430/py-R-FCN-multiGPU
PyTorchhttps://github.com/amdegroot/ssd.pytorch
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SSD512-pytorchhttps://github.com/lopuhin/ssd.pytorch
tensorflowhttps://github.com/gliese581gg/YOLO_tensorflow
PyTorchhttps://github.com/DavidTai416/Object-Detection-Development/blob/master
CAFFEhttps://github.com/philipperemy/yolo-9000
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PyTorchhttps://github.com/longcw/yolo2-pytorch
PyTorchhttps://github.com/marvis/pytorch-yolo2
PyCAFFEhttps://github.com/szq0214/DSOD
pytorchhttps://github.com/c0nn3r/RetinaNet
1https://github.com/kkufieta/CarND-Vehicle-Detection
2https://github.com/LeotisBuchanan/udacity_vehicle_detection
1https://github.com/xmprise/Vehicle_Detection_and_Tracking
1https://github.com/manutdzou/KITTI_SSD
1https://github.com/fregu856/2D_detection
1https://github.com/manutdzou/KITTI_FRC_detection
1https://github.com/yukitsuji/3D_CNN_tensorflow
1https://github.com/catpanda/lane_detection
1https://github.com/cguindel/eval_kitti
1https://github.com/omgteam/Didi-competition-solution
2https://github.com/sir-siemens/team-007
1https://github.com/CarND-Capstone-Defender/car-nd-capstone
2https://github.com/byronrwth/Udacity-SelfDrivingCar-Term2
YOLOhttps://github.com/aashay96/YOLO-Udacity
traffic light detectionhttps://github.com/awoodacrew/tldetect
final projecthttps://github.com/AndysDeepAbstractions/Early_Birds_CarND-Capstone
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pytorchhttps://github.com/ClementPinard/SfmLearner-Pytorch
pytorchhttps://github.com/zlmzju/fusenet
https://github.com/DavidTai416/Object-Detection-Development#4extra-reading-notes
csdnhttp://blog.csdn.net/zhang11wu4/article/details/53967688
zhihuhttps://zhuanlan.zhihu.com/p/31742364
zhihuhttps://zhuanlan.zhihu.com/p/31427288
zhihuhttps://zhuanlan.zhihu.com/p/29410169
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旷视,wechathttp://mp.weixin.qq.com/s/QJm7YoCYmiF0dX8uac5w4Q
csdnhttp://blog.csdn.net/zb1165048017/article/details/71104241
zhihuhttps://zhuanlan.zhihu.com/p/32247648
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https://github.com/DavidTai416/Object-Detection-Development#5very-recent-works
https://github.com/DavidTai416/Object-Detection-Development#a-for-2d-object-detection
Feature Selective Networks for Object Detectionhttps://arxiv.org/pdf/1711.08879.pdf
MegDet: A Large Mini-Batch Object Detectorhttps://arxiv.org/pdf/1711.07240.pdf
Deep Image Priorhttps://arxiv.org/pdf/1711.10925.pdf
An Analysis of Scale Invariance in Object Detection – SNIPhttps://arxiv.org/pdf/1711.08189.pdf
Receptive Field Block Net for Accurate and Fast Object Detectionhttps://arxiv.org/pdf/1711.07767.pdf
Single-Shot Refinement Neural Network for Object Detectionhttps://arxiv.org/pdf/1711.06897.pdf
Contextual Object Detection with a Few Relevant Neighborshttps://arxiv.org/pdf/1711.05705.pdf
Dynamic Zoom-in Network for Fast Object Detection in Large Imageshttps://arxiv.org/pdf/1711.05187.pdf
A Taught-Obesrve-Ask (TOA) Method for Object Detection with Critical Supervisionhttps://arxiv.org/pdf/1711.01043.pdf
Cascade Region Proposal and Global Context for Deep Object Detectionhttps://arxiv.org/pdf/1710.10749.pdf
Relation networkshttps://arxiv.org/pdf/1711.11575.pdf
Single Shot Text Detector with Regional Attentionhttps://arxiv.org/pdf/1709.00138.pdf
DSSDhttps://arxiv.org/pdf/1701.06659.pdf
RRChttps://arxiv.org/pdf/1704.05776.pdf
Gated DSODhttps://arxiv.org/pdf/1712.00886.pdf
https://github.com/DavidTai416/Object-Detection-Development#b-for-3d-object-detection
House 3D, a datasethttps://github.com/facebookresearch/House3D
Frustum PointNets for 3D Object Detection from RGB-D Datahttps://arxiv.org/pdf/1711.08488.pdf
VoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detectionhttps://arxiv.org/pdf/1711.06396.pdf
Single Multi-feature detector for Amodal 3D Object Detection in RGB-D Imageshttps://arxiv.org/pdf/1711.00238.pdf
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentationhttps://arxiv.org/pdf/1612.00593.pdf
3D Object Proposals using Stereo Imagery for Accurate Object Class Detectionhttps://arxiv.org/pdf/1608.07711.pdf
SSD-6D: Making RGB-Based 3D Detection and 6D Pose Estimation Great Againhttps://arxiv.org/pdf/1711.10006.pdf
https://github.com/DavidTai416/Object-Detection-Development#c-for-car-detection-especially
PointFusion: Deep Sensor Fusion for 3D Bounding Box Estimationhttps://arxiv.org/pdf/1711.10871.pdf
Joint 3D Proposal Generation and Object Detection from View Aggregationhttps://arxiv.org/pdf/1712.02294.pdf
Fusing Bird View LIDAR Point Cloud and Front View Camera Image for Deep Object Detectionhttps://arxiv.org/pdf/1711.06703.pdf
A Joint 3D-2D based Method for Free Space Detection on Roadshttps://arxiv.org/pdf/1711.02144.pdf
PointCNNhttps://arxiv.org/pdf/1801.07791.pdf
BoxCars: Improving Fine-Grained Recognition of Vehicles using 3D Bounding Boxes in Traffic Surveillancehttps://arxiv.org/pdf/1703.00686.pdf
3D Bounding Box Estimation Using Deep Learning and Geometryhttp://link.zhihu.com/?target=https%3A//arxiv.org/pdf/1612.00496
https://github.com/DavidTai416/Object-Detection-Development#d-other-useful-tools
Non-Localhttps://arxiv.org/pdf/1711.07971.pdf
Left-Right Skip-DenseNets for Coarse-to-Fine Object Categorizationhttps://arxiv.org/pdf/1710.10386.pdf
Learning by Asking Questionshttps://arxiv.org/pdf/1712.01238.pdf
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