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A discriminatively trained, multiscale, deformable part model

by Pedro Felzenszwalb, David Mcallester, Deva Ramanan - In IEEE Conference on Computer Vision and Pattern Recognition (CVPR-2008 , 2008
"... This paper describes a discriminatively trained, multiscale, deformable part model for object detection. Our system achieves a two-fold improvement in average precision over the best performance in the 2006 PASCAL person detection challenge. It also outperforms the best results in the 2007 challenge ..."
Abstract - Cited by 559 (11 self) - Add to MetaCart
This paper describes a discriminatively trained, multiscale, deformable part model for object detection. Our system achieves a two-fold improvement in average precision over the best performance in the 2006 PASCAL person detection challenge. It also outperforms the best results in the 2007

in the Deformable Parts Model?

by Santosh K. Divvala, Alexei Efros, Martial Hebert, Santosh K. Divvala, Alexei A. Efros, Martial Hebert
"... Abstract. The Deformable Parts Model (DPM) has recently emerged as a very useful and popular tool for tackling the intra-category diversity problem in object detection. In this paper, we summarize the key insights from our empirical analysis of the important elements constituting this detector. More ..."
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Abstract. The Deformable Parts Model (DPM) has recently emerged as a very useful and popular tool for tackling the intra-category diversity problem in object detection. In this paper, we summarize the key insights from our empirical analysis of the important elements constituting this detector

Active Deformable Part Models

by Menglong Zhu, Nikolay Atanasov, Kostas Daniilidis
"... This paper presents an active approach for part-based object detection, which optimizes the order of part filter evaluations and the time at which to stop and make a prediction. Statistics, describing the part responses, are learned from training data and are used to formalize the part scheduling pr ..."
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responses. The method is faster than cascade detection with deformable part models (which does not optimize the part order) with negligible loss in ac-curacy when evaluated on the PASCAL VOC 2007 and 2010 datasets. 1.

Deformable Part Models with CNN Features

by Pierre-andre ́ Savalle, Stavros Tsogkas, George Pap
"... Abstract. In this work we report on progress in integrating deep convo-lutional features with Deformable Part Models (DPMs). We substitute the Histogram-of-Gradient features of DPMs with Convolutional Neu-ral Network (CNN) features, obtained from the top-most, fifth, convolu-tional layer of Krizhevs ..."
Abstract - Cited by 5 (2 self) - Add to MetaCart
Abstract. In this work we report on progress in integrating deep convo-lutional features with Deformable Part Models (DPMs). We substitute the Histogram-of-Gradient features of DPMs with Convolutional Neu-ral Network (CNN) features, obtained from the top-most, fifth, convolu-tional layer

Active Deformable Part Models Inference

by Menglong Zhu, Nikolay Atanasov, Kostas Daniilidis
"... Abstract. This paper presents an active approach for part-based ob-ject detection, which optimizes the order of part filter evaluations and the time at which to stop and make a prediction. Statistics, describing the part responses, are learned from training data and are used to for-malize the part s ..."
Abstract - Cited by 1 (0 self) - Add to MetaCart
responses. The method is faster than cascade detection with deformable part models (which does not optimize the part order) with negligible loss in accuracy when evaluated on the PASCAL VOC 2007 and 2010 datasets. 1

How important are ‘deformable parts’ in the deformable parts model

by Santosh K. Divvala, Alexei A. Efros, Martial Hebert - In ECCV Workshop on Parts and Attributes , 2012
"... Abstract. The Deformable Parts Model (DPM) has recently emerged as a very useful and popular tool for tackling the intra-category diversity problem in object detection. In this paper, we summarize the key insights from our empirical analysis of the important elements constituting this detector. More ..."
Abstract - Cited by 42 (4 self) - Add to MetaCart
Abstract. The Deformable Parts Model (DPM) has recently emerged as a very useful and popular tool for tackling the intra-category diversity problem in object detection. In this paper, we summarize the key insights from our empirical analysis of the important elements constituting this detector

Segmentation-aware Deformable Part Models

by Eduard Trulls, Stavros Tsogkas, Iasonas Kokkinos, Alberto Sanfeliu, Francesc Moreno-noguer
"... In this work we propose a technique to combine bottom-up segmentation, coming in the form of SLIC superpixels, with sliding window detectors, such as Deformable Part Models (DPMs). The merit of our approach lies in ‘cleaning up ’ the low-level HOG features by exploiting the spatial support of SLIC s ..."
Abstract - Cited by 2 (1 self) - Add to MetaCart
In this work we propose a technique to combine bottom-up segmentation, coming in the form of SLIC superpixels, with sliding window detectors, such as Deformable Part Models (DPMs). The merit of our approach lies in ‘cleaning up ’ the low-level HOG features by exploiting the spatial support of SLIC

Spatiotemporal Deformable Part Models for Action Detection

by Yicong Tian, Rahul Sukthankar, Mubarak Shah
"... Deformable part models have achieved impressive performance for object detection, even on difficult image datasets. This paper explores the generalization of deformable part models from 2D images to 3D spatiotemporal volumes to better study their effectiveness for action detection in video. Actions ..."
Abstract - Cited by 36 (2 self) - Add to MetaCart
Deformable part models have achieved impressive performance for object detection, even on difficult image datasets. This paper explores the generalization of deformable part models from 2D images to 3D spatiotemporal volumes to better study their effectiveness for action detection in video. Actions

Cascade Object Detection with Deformable Part Models ∗

by Pedro F. Felzenszwalb, Ross B. Girshick, David Mcallester
"... We describe a general method for building cascade classifiers from part-based deformable models such as pictorial structures. We focus primarily on the case of star-structured models and show how a simple algorithm based on partial hypothesis pruning can speed up object detection by more than one or ..."
Abstract - Cited by 168 (5 self) - Add to MetaCart
We describe a general method for building cascade classifiers from part-based deformable models such as pictorial structures. We focus primarily on the case of star-structured models and show how a simple algorithm based on partial hypothesis pruning can speed up object detection by more than one

Deformable Parts Model Head Detections

by Ankan Bansal, Counting Human Detection , 2014
"... ● For crowds the bodies are are almost entirely occluded. ● Only heads visible. ..."
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● For crowds the bodies are are almost entirely occluded. ● Only heads visible.
Results 1 - 10 of 4,230,365