Nutrition5k: Towards Automatic Nutritional Understanding of Generic Food

Autor: Thames, Quin, Karpur, Arjun, Norris, Wade, Xia, Fangting, Panait, Liviu, Weyand, Tobias, Sim, Jack

Understanding the nutritional content of food from visual data is a challenging computer vision problem, with the potential to have a positive and widespread impact on public health. Studies in this area are limited to existing datasets in the field

Externí odkaz: http://arxiv.org/abs/2103.03375

Zoom Better to See Clearer: Human and Object Parsing with Hierarchical Auto-Zoom Net

Autor: Xia, Fangting, Wang, Peng, Chen, Liang-Chieh, Yuille, Alan L.

Parsing articulated objects, e.g. humans and animals, into semantic parts (e.g. body, head and arms, etc.) from natural images is a challenging and fundamental problem for computer vision. A big difficulty is the large variability of scale and locati

Externí odkaz: http://arxiv.org/abs/1511.06881

Pose-Guided Human Semantic Part Segmentation

Autor: Xia, Fangting

Publikováno v: Xia, Fangting. (2016). Pose-Guided Human Semantic Part Segmentation. UCLA: Statistics 0891. Retrieved from: http://www.escholarship.org/uc/item/34r7t3d3

Human semantic part segmentation and human pose estimation are two fundamental and complementary tasks in computer vision. The localization of joints in pose estimation can be much more accurate with the support of part segment consistency while the

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=od_______325::26ae9e46da761a04852f35b8cea6a781
http://www.escholarship.org/uc/item/34r7t3d3