SOTAVerified

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

Showing 211220 of 259 papers

TitleStatusHype
Precision and Adaptability of YOLOv5 and YOLOv8 in Dynamic Robotic Environments0
Prototipo de un Contador Bidireccional Automático de Personas basado en sensores de visión 3D0
P-YOLOv8: Efficient and Accurate Real-Time Detection of Distracted Driving0
Quantizing YOLOv7: A Comprehensive Study0
Q-YOLO: Efficient Inference for Real-time Object Detection0
Real-Time Automated donning and doffing detection of PPE based on Yolov4-tiny0
Real Time Multi-Class Object Detection and Recognition Using Vision Augmentation Algorithm0
0/1 Deep Neural Networks via Block Coordinate Descent0
Real-Time Object Detection and Localization in Compressive Sensed Video on Embedded Hardware0
Real-Time Object Detection and Recognition on Low-Compute Humanoid Robots using Deep Learning0
Show:102550
← PrevPage 22 of 26Next →

No leaderboard results yet.