Object Detection (1) - 모델 정리 및 비교

Object Detection 모델의 변화

R-CNN (2013)

• https://arxiv.org/pdf/1311.2524.pdf

Overfeat (2014)

• https://arxiv.org/pdf/1312.6229.pdf

Fast R-CNN (2015)

• https://arxiv.org/pdf/1504.08083.pdf

Fater R-CNN (2015)

• https://arxiv.org/pdf/1506.01497.pdf

OHEM (2016)

• https://arxiv.org/pdf/1604.03540.pdf

YOLO v1 (2016)

• https://arxiv.org/pdf/1506.02640.pdf

SSD (2016)

• https://arxiv.org/pdf/1512.02325.pdf

R-FCN (2016)

• https://arxiv.org/pdf/1605.06409.pdf

YOLO v2 (2017)

• https://arxiv.org/pdf/1612.08242.pdf

FPN (2017)

• https://arxiv.org/pdf/1612.03144.pdf

RetinaNet (2017)

• https://arxiv.org/pdf/1708.02002.pdf

Mask R-CNN (2017)

• https://arxiv.org/pdf/1703.06870.pdf

YOLO v3 (2018)

• https://arxiv.org/pdf/1804.02767.pdf

RefineDet (2018)

• https://arxiv.org/pdf/1711.06897.pdf

M2Det (2019)

• https://arxiv.org/pdf/1811.04533.pdf

YOLO v4 (2020)

• https://arxiv.org/pdf/2004.10934v1.pdf

EfficientDet (2020)

• https://arxiv.org/pdf/1911.09070.pdf

DETR (2020)

• https://arxiv.org/pdf/2005.12872.pdf

Deformable DETR (2020) -> Swin Transformer(2021) -> YOLOR (2021)

YOLO 모델 비교

• 참고 문헌
  -> https://herbwood.tistory.com/2, 'Object Detection' 시리즈
  -> https://leedakyeong.tistory.com/entry/Object-Detection-YOLO-v1v6-%EB%B9%84%EA%B5%90
  -> https://leedakyeong.tistory.com/entry/Object-Detection-YOLO-v1v6-%EB%B9%84%EA%B5%902