Probabilistic Watershed: Sampling all spanning forests for seeded segmentation and semi-supervised learning

6 November 2019

Papers citing "Probabilistic Watershed: Sampling all spanning forests for seeded segmentation and semi-supervised learning"

9 / 9 papers shown

Title
End-to-End Learned Random Walker for Seeded Image Segmentation Lorenzo Cerrone Alexander Zeilmann Fred Hamprecht 45 20 0 22 May 2019
Stochastic Distance Transform Johan Öfverstedt Joakim Lindblad Natasa Sladoje 32 2 0 18 Oct 2018
Differentiable Dynamic Programming for Structured Prediction and Attention A. Mensch Mathieu Blondel 58 131 0 11 Feb 2018
Learning random-walk label propagation for weakly-supervised semantic segmentation Paul Vernaza Manmohan Chandraker 81 253 0 01 Feb 2018
Learned Watershed: End-to-End Learning of Seeded Segmentation Steffen Wolf Lukas Schott Ullrich Kothe Fred Hamprecht 35 35 0 07 Apr 2017
Deep Watershed Transform for Instance Segmentation Min Bai R. Urtasun ISeg SSeg 110 522 0 24 Nov 2016
Sinkhorn Distances: Lightspeed Computation of Optimal Transportation Distances Marco Cuturi OT 197 4,251 0 04 Jun 2013
A bag-of-paths framework for network data analysis Kevin Françoisse Ilkka Kivimäki Amin Mantrach F. Rossi M. Saerens 44 39 0 27 Feb 2013
Developments in the theory of randomized shortest paths with a comparison of graph node distances Ilkka Kivimäki Masashi Shimbo M. Saerens OT 67 84 0 07 Dec 2012