Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Benjamin Packer"'
Publikováno v:
NIPS
Discriminative tasks, including object categorization and detection, are central components of high-level computer vision. However, sometimes we are interested in a finer-grained characterization of the object's properties, such as its pose or articu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::44da5f8318c668c4763f23306a979192
https://doi.org/10.1007/s11263-009-0228-y
https://doi.org/10.1007/s11263-009-0228-y
Publikováno v:
Modeling Latent Variable Uncertainty for Loss-based Learning.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=erc_________::929b9be4d9c4372ba6cdb1d6704c0d70
Publikováno v:
CVPR
The bounding box representation employed by many popular object detection models [3, 6] implicitly assumes all pixels inside the box belong to the object. This assumption makes this representation less robust to the object with occlusion [16]. In thi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::54105f40d092adc9446310f9cd006048
https://doi.org/10.1109/cvpr.2011.5995623
https://doi.org/10.1109/cvpr.2011.5995623
Publikováno v:
ICML
We present a new machine learning framework called "self-taught learning" for using unlabeled data in supervised classification tasks. We do not assume that the unlabeled data follows the same class labels or generative distribution as the labeled da
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fbe49d7f515e7b4490c0ed1fa5874643
https://doi.org/10.1145/1273496.1273592
https://doi.org/10.1145/1273496.1273592