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Author |
David Vazquez; Jiaolong Xu; Sebastian Ramos; Antonio Lopez; Daniel Ponsa |
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Title |
Weakly Supervised Automatic Annotation of Pedestrian Bounding Boxes |
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Conference Article |
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Year |
2013 |
Publication |
CVPR Workshop on Ground Truth – What is a good dataset? |
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706 - 711 |
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Pedestrian Detection; Domain Adaptation |
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Abstract  |
Among the components of a pedestrian detector, its trained pedestrian classifier is crucial for achieving the desired performance. The initial task of the training process consists in collecting samples of pedestrians and background, which involves tiresome manual annotation of pedestrian bounding boxes (BBs). Thus, recent works have assessed the use of automatically collected samples from photo-realistic virtual worlds. However, learning from virtual-world samples and testing in real-world images may suffer the dataset shift problem. Accordingly, in this paper we assess an strategy to collect samples from the real world and retrain with them, thus avoiding the dataset shift, but in such a way that no BBs of real-world pedestrians have to be provided. In particular, we train a pedestrian classifier based on virtual-world samples (no human annotation required). Then, using such a classifier we collect pedestrian samples from real-world images by detection. After, a human oracle rejects the false detections efficiently (weak annotation). Finally, a new classifier is trained with the accepted detections. We show that this classifier is competitive with respect to the counterpart trained with samples collected by manually annotating hundreds of pedestrian BBs. |
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Portland; Oregon; June 2013 |
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IEEE |
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English |
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CVPRW |
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ADAS; 600.054; 600.057; 601.217 |
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ADAS @ adas @ VXR2013a |
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2219 |
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Author |
Cesar de Souza; Adrien Gaidon; Eleonora Vig; Antonio Lopez |
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Title |
Sympathy for the Details: Dense Trajectories and Hybrid Classification Architectures for Action Recognition |
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Conference Article |
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Year |
2016 |
Publication |
14th European Conference on Computer Vision |
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697-716 |
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Action recognition in videos is a challenging task due to the complexity of the spatio-temporal patterns to model and the difficulty to acquire and learn on large quantities of video data. Deep learning, although a breakthrough for image classification and showing promise for videos, has still not clearly superseded action recognition methods using hand-crafted features, even when training on massive datasets. In this paper, we introduce hybrid video classification architectures based on carefully designed unsupervised representations of hand-crafted spatio-temporal features classified by supervised deep networks. As we show in our experiments on five popular benchmarks for action recognition, our hybrid model combines the best of both worlds: it is data efficient (trained on 150 to 10000 short clips) and yet improves significantly on the state of the art, including recent deep models trained on millions of manually labelled images and videos. |
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Amsterdam; The Netherlands; October 2016 |
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ECCV |
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ADAS; 600.076; 600.085 |
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Call Number |
Admin @ si @ SGV2016 |
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2824 |
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Author |
Judit Martinez; Eva Costa; P. Herreros; Antonio Lopez; Juan J. Villanueva |
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Title |
TV-Screen Quality Inspection by Artificial Vision |
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Conference Article |
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2003 |
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Proceedings SPIE 5132, Sixth International Conference on Quality Control by Artificial Vision (QCAV 2003) |
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A real-time vision system for TV screen quality inspection is introduced. The whole system consists of eight cameras and one processor per camera. It acquires and processes 112 images in 6 seconds. The defects to be inspected can be grouped into four main categories (bubble, line-out, line reduction and landing) although there exists a large variability among each particular type of defect. The complexity of the whole inspection process has been reduced by dividing images into smaller ones and grouping the defects into frequency and intensity relevant ones. Tools such as mathematical morphology, Fourier transform, profile analysis and classification have been used. The performance of the system has been successfully proved against human operators in normal production conditions. |
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Gatlinburg, (EEUU) |
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ADAS @ adas @ MCH2003a |
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393 |
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Author |
Felipe Lumbreras; Xavier Roca; Daniel Ponsa; Robert Benavente; Judit Martinez; Silvia Sanchez; Coen Antens; Juan J. Villanueva |
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Title |
Visual Inspection of Safety Belts |
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Conference Article |
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Year |
2001 |
Publication |
International Conference on Quality Control by Artificial Vision |
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2 |
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526–531 |
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France |
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QCAV |
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ADAS;ISE;CIC |
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ADAS @ adas @ LRP2001 |
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122 |
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Author |
Petia Radeva; Joan Serrat |
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Title |
Rubber Snake: Implementation on Signed Distance Potential. |
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1993 |
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Vision Conference |
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187-194 |
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Zurich, Switzerland. |
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ADAS;MILAB |
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ADAS @ adas @ RaS1993 |
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170 |
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Author |
X. Orriols; Ricardo Toledo; X. Binefa; Petia Radeva; Jordi Vitria; Juan J. Villanueva |
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Title |
Probabilistic Saliency Approach for Elongated Structure Detection using Deformable Models. |
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Conference Article |
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Year |
2000 |
Publication |
15 th International Conference on Pattern Recognition |
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3 |
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1006-1009 |
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Barcelona. |
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ICPR |
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OR;MILAB;ADAS;MV |
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BCNPCL @ bcnpcl @ OTB2000 |
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224 |
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Author |
Ricardo Toledo; X. Orriols; Petia Radeva; X. Binefa; Jordi Vitria; Cristina Cañero; Juan J. Villanueva |
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Title |
Eigensnakes for vessel segmentation in angiography. |
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Conference Article |
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Year |
2000 |
Publication |
15 th International Conference on Pattern Recognition |
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4 |
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340-343 |
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Barcelona. |
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OR;MILAB;ADAS;MV |
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BCNPCL @ bcnpcl @ TOR2000 |
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235 |
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Author |
A. Pujol; Felipe Lumbreras; X. Varona; Juan J. Villanueva |
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Title |
Locating people in indoor scenes for real applications. |
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Conference Article |
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2000 |
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15 th International Conference on Pattern Recognition |
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4 |
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632-635 |
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Barcelona. |
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ADAS |
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ADAS @ adas @ PLV2000 |
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237 |
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Author |
Cristina Cañero; Petia Radeva; Ricardo Toledo; Juan J. Villanueva; J. Mauri |
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Title |
3D Curve Reconstruction by Biplane Snakes. |
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Conference Article |
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2000 |
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15 th International Conference on Pattern Recognition |
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4 |
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563-566 |
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Barcelona. |
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MILAB;ADAS |
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BCNPCL @ bcnpcl @ CRT2000 |
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238 |
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Author |
M.J. Yzuel; J. Pladellorens; Joan Serrat; A. Dupuy |
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Title |
Application restauration and edge detection techniques in the calculation of left ventricular volumes. |
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1993 |
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Optics in Medicine, Biology and Environmental Research : Selected contributions to the first International Conference on Optics within Life Sciences (OWLS I) |
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374-375 |
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Elsevier |
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ADAS @ adas @ YPS1993 |
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244 |
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