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Real-Time Object Detection

28 papers with code · Computer Vision
Subtask of Object Detection

Real-time object detection is the task of doing object detection in real-time with fast inference while maintaining a base level of accuracy.

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Greatest papers with code

R-FCN: Object Detection via Region-based Fully Convolutional Networks

NeurIPS 2016 facebookresearch/detectron

In contrast to previous region-based detectors such as Fast/Faster R-CNN that apply a costly per-region subnetwork hundreds of times, our region-based detector is fully convolutional with almost all computation shared on the entire image.

REAL-TIME OBJECT DETECTION

Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks

NeurIPS 2015 facebookresearch/detectron

In this work, we introduce a Region Proposal Network (RPN) that shares full-image convolutional features with the detection network, thus enabling nearly cost-free region proposals.

REAL-TIME OBJECT DETECTION

You Only Look Once: Unified, Real-Time Object Detection

CVPR 2016 thtrieu/darkflow

A single neural network predicts bounding boxes and class probabilities directly from full images in one evaluation.

REAL-TIME OBJECT DETECTION

YOLOv3: An Incremental Improvement

8 Apr 2018qqwweee/keras-yolo3

At 320x320 YOLOv3 runs in 22 ms at 28. 2 mAP, as accurate as SSD but three times faster.

REAL-TIME OBJECT DETECTION

Objects as Points

16 Apr 2019xingyizhou/CenterNet

We model an object as a single point --- the center point of its bounding box.

KEYPOINT DETECTION REAL-TIME OBJECT DETECTION

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

CVPR 2019 tensorflow/tpu

Here we aim to learn a better architecture of feature pyramid network for object detection.

#10 best model for Real-Time Object Detection on COCO (MAP metric)

NEURAL ARCHITECTURE SEARCH REAL-TIME OBJECT DETECTION

CornerNet-Lite: Efficient Keypoint Based Object Detection

18 Apr 2019princeton-vl/CornerNet-Lite

Together these two variants address the two critical use cases in efficient object detection: improving efficiency without sacrificing accuracy, and improving accuracy at real-time efficiency.

REAL-TIME OBJECT DETECTION

Receptive Field Block Net for Accurate and Fast Object Detection

ECCV 2018 ruinmessi/RFBNet

Current top-performing object detectors depend on deep CNN backbones, such as ResNet-101 and Inception, benefiting from their powerful feature representations but suffering from high computational costs.

REAL-TIME OBJECT DETECTION

Pelee: A Real-Time Object Detection System on Mobile Devices

NeurIPS 2018 osmr/imgclsmob

In this study, we propose an efficient architecture named PeleeNet, which is built with conventional convolution instead.

REAL-TIME OBJECT DETECTION