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Real-Time Object Detection

Real-Time Object Detection is a computer vision task that involves identifying and locating objects of interest in real-time video sequences with fast inference while maintaining a base level of accuracy.

This is typically solved using algorithms that combine object detection and tracking techniques to accurately detect and track objects in real-time. They use a combination of feature extraction, object proposal generation, and classification to detect and localize objects of interest.

( Image credit: CenterNet )

Papers

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Showing 76–100 of 259 papers

TitleStatusHype
End-to-End Object Detection with TransformersCode1
MODIPHY: Multimodal Obscured Detection for IoT using PHantom Convolution-Enabled Faster YOLOCode1
Automated detection of COVID-19 cases using deep neural networks with X-ray imagesCode1
HarDNet: A Low Memory Traffic NetworkCode1
Towards Streaming PerceptionCode1
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal NetworksCode1
A Unified Multi-scale Deep Convolutional Neural Network for Fast Object DetectionCode0
SqueezeDet: Unified, Small, Low Power Fully Convolutional Neural Networks for Real-Time Object Detection for Autonomous DrivingCode0
SpineNet: Learning Scale-Permuted Backbone for Recognition and LocalizationCode0
Tiny SSD: A Tiny Single-shot Detection Deep Convolutional Neural Network for Real-time Embedded Object DetectionCode0
DeNet: Scalable Real-time Object Detection with Directed Sparse SamplingCode0
Attentional PointNet for 3D-Object Detection in Point CloudsCode0
SlimYOLOv3: Narrower, Faster and Better for Real-Time UAV ApplicationsCode0
R-FCN: Object Detection via Region-based Fully Convolutional NetworksCode0
DaDe: Delay-adaptive Detector for Streaming PerceptionCode0
Gold-YOLO: Efficient Object Detector via Gather-and-Distribute MechanismCode0
Relief R-CNN : Utilizing Convolutional Features for Fast Object DetectionCode0
Receptive Field Block Net for Accurate and Fast Object DetectionCode0
Real Time Object Detection System with YOLO and CNN Models: A ReviewCode0
Real-Time Object Detection on High-Voltage Powerlines Using an Unmanned Aerial Vehicle (UAV)Code0
Replication Study and Benchmarking of Real-Time Object Detection ModelsCode0
R-TOD: Real-Time Object Detector with Minimized End-to-End Delay for Autonomous DrivingCode0
Context-aware Multi-Model Object Detection for Diversely Heterogeneous Compute SystemsCode0
Real-Time Brain Tumor Detection in Intraoperative Ultrasound Using YOLO11: From Model Training to Deployment in the Operating RoomCode0
Fast YOLO: A Fast You Only Look Once System for Real-time Embedded Object Detection in VideoCode0
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