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You Only Look Once: Unified, Real-Time Object Detection

Authors: Joseph Redmon, Santosh Divvala, Ross Girshick, Ali Farhadi Year: 2016 Citations: 30,000+

Summary

Single-stage object detector framing detection as regression. Predicts bounding boxes and class probabilities directly from full image in one forward pass. Enables real-time detection.

Key Concepts

  • Single-Stage Detection: Direct regression without region proposals
  • End-to-End Regression: Detection as regression problem
  • Real-Time Performance: Fast enough for live video
  • Spatial Awareness: Grid divides image for predictions
  • Global Context: Entire image context aware
  • Simplicity: Single CNN for direct output

Impact

  • 30,000+ citations
  • Introduced single-stage detection paradigm
  • Enabled real-time object detection systems
  • Faster than R-CNN variants
  • YOLO v2, v3, v4, v5 widely deployed
  • Influenced SSD and single-stage methods
  • Critical for real-world applications
  • R-CNN (Girshick et al., 2014)
  • Faster R-CNN (Ren et al., 2015)
  • SSD: Single Shot Detector (Liu et al., 2016)