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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 151–175 of 259 papers

TitleStatusHype
Asymmetric Pruning for Learning Cascade Detectors—0
ATLASv2: LLM-Guided Adaptive Landmark Acquisition and Navigation on the Edge—0
AU-AIR: A Multi-modal Unmanned Aerial Vehicle Dataset for Low Altitude Traffic Surveillance—0
Automatic Cattle Identification using YOLOv5 and Mosaic Augmentation: A Comparative Analysis—0
A Vision-Enabled Prosthetic Hand for Children with Upper Limb Disabilities—0
BandRe: Rethinking Band-Pass Filters for Scale-Wise Object Detection Evaluation—0
BiSwift: Bandwidth Orchestrator for Multi-Stream Video Analytics on Edge—0
CF-DETR: Coarse-to-Fine Transformer for Real-Time Object Detection—0
Check Your Other Door! Creating Backdoor Attacks in the Frequency Domain—0
Computer Vision for Construction Progress Monitoring: A Real-Time Object Detection Approach—0
CorrDiff: Adaptive Delay-aware Detector with Temporal Cue Inputs for Real-time Object Detection—0
Dataset and Benchmarking of Real-Time Embedded Object Detection for RoboCup SSL—0
DeepLOC: Deep Learning-based Bone Pathology Localization and Classification in Wrist X-ray Images—0
Deep SCNN-based Real-time Object Detection for Self-driving Vehicles Using LiDAR Temporal Data—0
Deriving star cluster parameters with convolutional neural networks. II. Extinction and cluster/background classification—0
A Deep Learning Framework for Detection of Targets in Thermal Images to Improve Firefighting—0
Detection of Rail Line Track and Human Beings Near the Track to Avoid Accidents—0
DS MYOLO: A Reliable Object Detector Based on SSMs for Driving Scenarios—0
Dynamic Zoom-in Network for Fast Object Detection in Large Images—0
Edge Network-Assisted Real-Time Object Detection Framework for Autonomous Driving—0
Enabling Efficient Processing of Spiking Neural Networks with On-Chip Learning on Commodity Neuromorphic Processors for Edge AI Systems—0
Exploring Machine Learning Engineering for Object Detection and Tracking by Unmanned Aerial Vehicle (UAV)—0
Factorial Convolution Neural Networks—0
FasterX: Real-Time Object Detection Based on Edge GPUs for UAV Applications—0
Fast Learning and Prediction for Object Detection using Whitened CNN Features—0
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