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 151160 of 259 papers

TitleStatusHype
Asymmetric Pruning for Learning Cascade Detectors0
ATLASv2: LLM-Guided Adaptive Landmark Acquisition and Navigation on the Edge0
AU-AIR: A Multi-modal Unmanned Aerial Vehicle Dataset for Low Altitude Traffic Surveillance0
Automatic Cattle Identification using YOLOv5 and Mosaic Augmentation: A Comparative Analysis0
A Vision-Enabled Prosthetic Hand for Children with Upper Limb Disabilities0
BandRe: Rethinking Band-Pass Filters for Scale-Wise Object Detection Evaluation0
BiSwift: Bandwidth Orchestrator for Multi-Stream Video Analytics on Edge0
CF-DETR: Coarse-to-Fine Transformer for Real-Time Object Detection0
Check Your Other Door! Creating Backdoor Attacks in the Frequency Domain0
Computer Vision for Construction Progress Monitoring: A Real-Time Object Detection Approach0
Show:102550
← PrevPage 16 of 26Next →

No leaderboard results yet.