What, where and how many? Combining object detectors and CRFs Ladick, L'Ubor (Oxford Brookes University, United Kingdom); Sturgess, Paul ; Alahari, Karteek ; Russell, Chris ; Torr, Philip H. S. Source: Lecture Notes in Computer Science (including subseries Lecture Not ...
Graph cut based inference with co-occurrence statistics Ladicky, Lubor (Oxford Brookes, United Kingdom); Russell, Chris ; Kohli, Pushmeet ; Torr, Philip H. S. Source: Lecture Notes in Computer Science (including subseries Lecture Note ...
TextonBoost for image understanding: Multi-class object recognition and segmentation by jointly modeling texture, layout, and context Shotton, Jamie (Machine Intelligence Laboratory, University of Cambridge, Trumpington Street, Cambridge CB2 1PZ, United Kingdom); Winn, John ; Rother, Ca ...
Superpixel - based object class segmentation using conditional random fields Xi Li; Sahbi, H.; Acoustics, Speech and Signal Processing (ICASSP), 2011 IEEE International Conference on Digital Object Identifier: 10.1109/ICASSP.2011.5946600 Publication Year: 2011 , Page(s): ...
标题: Learning and incorporating top - down cues in image segmentation 作者: He XM; Zemel RS; Ray D 编者: Leonardis A; Bischof H; Pinz A 会议名称: 9th European Conference on Computer Vision (ECCV 2006) 会议地点: Graz, AUSTRIA 会议日期: MAY 07-13, 2006 会议赞助 ...
Multiscale conditional random fields for image labeling Xuming He; Zemel, R.S.; Carreira-Perpinan, M.A.; Computer Vision and Pattern Recognition, 2004. CVPR 2004. Proceedings of the 2004 IEEE Computer Society Conference on Volume: 2 Digital Object Identifier: 10.1109/CVPR ...
A Multiple Conditional Random Fields Ensemble Model for Urban Area Detection in Remote Sensing Optical Images Ping Zhong; Runsheng Wang; Geoscience and Remote Sensing , IEEE Transactions on Volume: 45 , Issue: 12 , Part: 1 Digital Object Identifier: 10. ...