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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

Showing 150 of 259 papers

TitleStatusHype
YOLOv9: Learning What You Want to Learn Using Programmable Gradient InformationCode16
YOLOv10: Real-Time End-to-End Object DetectionCode11
LW-DETR: A Transformer Replacement to YOLO for Real-Time DetectionCode9
DETRs Beat YOLOs on Real-time Object DetectionCode8
D-FINE: Redefine Regression Task in DETRs as Fine-grained Distribution RefinementCode7
YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectorsCode7
YOLOv6: A Single-Stage Object Detection Framework for Industrial ApplicationsCode5
YOLOv6 v3.0: A Full-Scale ReloadingCode5
YOLOv13: Real-Time Object Detection with Hypergraph-Enhanced Adaptive Visual PerceptionCode5
DEIM: DETR with Improved Matching for Fast ConvergenceCode5
Real-time Transformer-based Open-Vocabulary Detection with Efficient Fusion HeadCode5
A ConvNet for the 2020sCode5
Detectron2 Object Detection & Manipulating Images using CartoonizationCode4
DAMO-YOLO : A Report on Real-Time Object Detection DesignCode4
DINO: DETR with Improved DeNoising Anchor Boxes for End-to-End Object DetectionCode4
PP-YOLOE: An evolved version of YOLOCode4
RTMDet: An Empirical Study of Designing Real-Time Object DetectorsCode4
Vision Transformer Adapter for Dense PredictionsCode3
EfficientDet: Scalable and Efficient Object DetectionCode3
YOLOv4: Optimal Speed and Accuracy of Object DetectionCode3
Workshop on Autonomous Driving at CVPR 2021: Technical Report for Streaming Perception ChallengeCode3
Deformable DETR: Deformable Transformers for End-to-End Object DetectionCode3
FedPylot: Navigating Federated Learning for Real-Time Object Detection in Internet of VehiclesCode2
Real-time Object Detection for Streaming PerceptionCode2
Focal Loss for Dense Object DetectionCode2
Multi-Branch Auxiliary Fusion YOLO with Re-parameterization Heterogeneous Convolutional for accurate object detectionCode2
Objects as PointsCode2
YOLOv5-6D: Advancing 6-DoF Instrument Pose Estimation in Variable X-Ray Imaging GeometriesCode2
YOLO11-JDE: Fast and Accurate Multi-Object Tracking with Self-Supervised Re-IDCode2
Swin Transformer: Hierarchical Vision Transformer using Shifted WindowsCode2
YOLO-MS: Rethinking Multi-Scale Representation Learning for Real-time Object DetectionCode2
Slim-neck by GSConv: A lightweight-design for real-time detector architecturesCode2
SuperYOLO: Super Resolution Assisted Object Detection in Multimodal Remote Sensing ImageryCode2
HarDNet: A Low Memory Traffic NetworkCode1
RegionCLIP: Region-based Language-Image PretrainingCode1
HIC-YOLOv5: Improved YOLOv5 For Small Object DetectionCode1
FOVEA: Foveated Image Magnification for Autonomous NavigationCode1
Real-Time Polyp Detection, Localization and Segmentation in Colonoscopy Using Deep LearningCode1
Robust and Efficient Post-Processing for Video Object Detection (REPP)Code1
RCS-YOLO: A Fast and High-Accuracy Object Detector for Brain Tumor DetectionCode1
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal NetworksCode1
CSPNet: A New Backbone that can Enhance Learning Capability of CNNCode1
Parallel Residual Bi-Fusion Feature Pyramid Network for Accurate Single-Shot Object DetectionCode1
RT-DATR:Real-time Unsupervised Domain Adaptive Detection Transformer with Adversarial Feature LearningCode1
Contour Proposal Networks for Biomedical Instance SegmentationCode1
DPNet: Dual-Path Network for Real-time Object Detection with Lightweight AttentionCode1
Non-deep NetworksCode1
An Energy and GPU-Computation Efficient Backbone Network for Real-Time Object DetectionCode1
CST-YOLO: A Novel Method for Blood Cell Detection Based on Improved YOLOv7 and CNN-Swin TransformerCode1
Neural Compression and Filtering for Edge-assisted Real-time Object Detection in Challenged NetworksCode1
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