Zobrazeno 1 - 10
of 11
pro vyhledávání: '"Yueying Kao"'
Publikováno v:
AAAI
Monocular object pose estimation is an important yet challenging computer vision problem. Depth features can provide useful information for pose estimation. However, existing methods rely on real depth images to extract depth features, leading to its
Autor:
Yueying Kao, Bowen Pan, Miao Xu, Jiangjing Lyu, Xiangyu Zhu, Yuanzhang Chang, Xiaobo Li, Zhen Lei
Publikováno v:
IEEE Transactions on Image Processing. :1-1
In 3D face reconstruction, orthogonal projection has been widely employed to substitute perspective projection to simplify the fitting process. This approximation performs well when the distance between camera and face is far enough. However, in some
Publikováno v:
IEEE Transactions on Systems, Man, and Cybernetics: Systems. 47:648-659
The task of semantic segmentation is to infer a predefined category label for each pixel in the image. For most cases, image segmentation is established as a fully supervised task. These methods all built on the basis of having access to sufficient p
Autor:
Yueying Kao, Sunghoon Hong, Ran He, Minsu Ahn, Dongqing Zou, Wang Qiang, Weiming Li, Zairan Wang
Publikováno v:
IJCAI
Automatic object viewpoint estimation from a single image is an important but challenging problem in machine intelligence community. Although impressive performance has been achieved, current state-of-the-art methods still have difficulty to deal wit
Publikováno v:
IJCAI
Object pose estimation from a single image is a fundamental and challenging problem in computer vision and robotics. Generally, current methods treat pose estimation as a classification or a regression problem. However, regression based methods usual
Publikováno v:
Medical Imaging: Computer-Aided Diagnosis
In this paper, we investigated the problem of diagnostic lung nodule malignancy prediction using thoracic Computed Tomography (CT) screening. Unlike most existing studies classify the nodules into two types benign and malignancy, we interpreted the n
Publikováno v:
ICASSP
Image cropping is a fundamental task in image editing to enhance the aesthetic quality of images. In this paper, we propose an automatic image cropping technique based on aesthetic map and gradient energy map. Instead of utilizing aesthetic rules in
Aesthetic image analysis has attracted much attention in recent years. However, assessing the aesthetic quality and assigning an aesthetic score are challenging problems. In this paper, we propose a novel framework for assessing the aesthetic quality
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ab60b94d005c8204d36f976ed035298f
https://eprints.bbk.ac.uk/id/eprint/15178/1/15178.pdf
https://eprints.bbk.ac.uk/id/eprint/15178/1/15178.pdf
Human beings often assess the aesthetic quality of an image coupled with the identification of the image's semantic content. This paper addresses the correlation issue between automatic aesthetic quality assessment and semantic recognition. We cast t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::28ef998cb0a94516ac3719345f7f013e
http://arxiv.org/abs/1604.04970
http://arxiv.org/abs/1604.04970
Publikováno v:
ICIP
Aesthetic image analysis has drawn much attention in recent years. However, assessing the aesthetic quality especially aesthetic score prediction is a challenging problem. In this paper, we interpret aesthetic quality assessment as a regression probl