Publications
C
Arnab, A, Zheng, S, Jayasumana, S, Romera-paredes, B, Kirillov, A, Savchynskyy, B, Rother, C, Kahl, F and Torr, P (2018).
Conditional Random Fields Meet Deep Neural Networks for Semantic Segmentation.
Cvpr.
XX 1–15.
http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.308.8889&rep=rep1&type=pdf%0Ahttp://dx.doi.org/10.1109/CVPR.2012.6248050 D
Zheng, S, Cheng, M Ming, Warrell, J, Sturgess, P, Vineet, V, Rother, C and Torr, P H S (2014).
Dense semantic image segmentation with objects and attributes.
Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. 3214–3221.
http://www.robots.ox.ac.uk/˜tvg/http://tu-dresden.de/inf/cvld O
Zheng, S, Prisacariu, V Adrian, Averkiou, M, Cheng, M Ming, Mitra, N J, Shotton, J, Torr, P H S and Rother, C (2015).
Object proposals estimation in depth image using compact 3D shape manifolds.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).
9358 196–208
P
Mitra, N J, Stam, J, Xu, K, Cheng, M - M, Prisacariu, V Adrian, Zheng, S, Torr, P H S and Rother, C (2015).
Pacific Graphics 2015 DenseCut: Densely Connected CRFs for Realtime GrabCut.
34.
http://mftp.mmcheng.net/Papers/DenseCut.pdf