@proceedings {1883, title = {Scene-Domain Active Part Models for Object Representation}, year = {2015}, month = {12/2015}, pages = { 2497 - 2505 }, address = {Santiago, Chile}, abstract = {
In this paper, we are interested in enhancing the expressivity\ and robustness of part-based models for object representation,\ in the common scenario where the training data\ are based on 2D images. To this end, we propose scene-domain\ active part models (SDAPM), which reconstruct\ and characterize the 3D geometric statistics between object{\textquoteright}s\ parts in 3D scene-domain by using 2D training data\ in the image-domain alone. And on top of this, we explicitly\ model and handle occlusions in SDAPM. Together with the\ developed learning and inference algorithms, such a model\ provides rich object descriptions, including 2D object and\ parts localization, 3D landmark shape and camera viewpoint,\ which offers an effective representation to various image\ understanding tasks, such as object and parts detection,\ 3D landmark shape and viewpoint estimation from images.\ Experiments on the above tasks show that SDAPM outperforms\ previous part-based models, and thus demonstrates\ the potential of the proposed technique.
}, doi = {10.1109/ICCV.2015.287}, url = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=7410644\&tag=1}, author = {Zhou Ren and Chaohui Wang and Alan Yuille} }