TY - GEN
T1 - Multi-instance object segmentation with exemplars
AU - He, Xuming
AU - Gould, Stephen
PY - 2013
Y1 - 2013
N2 - We address the problem of joint detection and segmentation of multiple object instances in an image, a key step towards scene understanding. Inspired by data-driven methods, we propose an exemplar-based approach to the task of multi-instance segmentation using a small set of annotated reference images. We design a novel CRF model that jointly models object appearance, shape deformation, and object occlusion at the super pixel level. To tackle the challenging MAP inference problem, we derive an alternating procedure that interleaves object segmentation and layout adaptation.
AB - We address the problem of joint detection and segmentation of multiple object instances in an image, a key step towards scene understanding. Inspired by data-driven methods, we propose an exemplar-based approach to the task of multi-instance segmentation using a small set of annotated reference images. We design a novel CRF model that jointly models object appearance, shape deformation, and object occlusion at the super pixel level. To tackle the challenging MAP inference problem, we derive an alternating procedure that interleaves object segmentation and layout adaptation.
UR - http://www.scopus.com/inward/record.url?scp=84897492442&partnerID=8YFLogxK
U2 - 10.1109/ICCVW.2013.9
DO - 10.1109/ICCVW.2013.9
M3 - Conference contribution
SN - 9781479930227
T3 - Proceedings of the IEEE International Conference on Computer Vision
SP - 1
EP - 4
BT - Proceedings - 2013 IEEE International Conference on Computer Vision Workshops, ICCVW 2013
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2013 14th IEEE International Conference on Computer Vision Workshops, ICCVW 2013
Y2 - 1 December 2013 through 8 December 2013
ER -