Object Detection with Discriminatively Trained Part-Based Models | VitaVision
PaperIEEE TPAMI · 2010

Object Detection with Discriminatively Trained Part-Based Models

Pedro F. FelzenszwalbRoss GirshickDavid McAllesterDeva Ramanan
DOIView in graph
1page built on it
1more page cites it
1narrative
3registry papers cite it

In the Atlas

AlgorithmPrimary source of
Deformable Part Models

Detect a target object class in arbitrary images by scoring every position and scale in a HOG feature pyramid with a mixture of star-structured part-based templates — a coarse root filter and.

Cited as a reference by 1 page, grouped by domain

Detection 1
YOLOv1

Appears in 1 narrative

NarrativeDetection, Removing the Machinery

Lineage

Papers in the Atlas registry only · one dot per paper
Built upon by · 3
’01’02’03’04’05’06’07’08’09’10’11’12’13’14’15’16’17You Only Look Once: Unified, Real-Time Object Detection (2016)Feature Pyramid Networks for Object Detection (2017)Focal Loss for Dense Object Detection (2017)Rapid object detection using a boosted cascade of simple features (2001)Distinctive Image Features from Scale-Invariant Keypoints (2004)Histograms of Oriented Gradients for Human Detection (2005)