Higher Order Potentials in End-to-End Trainable Conditional Random Fields

By Anurag Arnab, Sadeep Jayasumana, Shuai Zheng, Philip H. S. Torr. 2015

23 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Liang-Chieh Chen
2. Anurag Arnab
3. Philip H. S. Torr
4. Falong Shen
5. Wenguan Wang
6. Gang Zeng
7. Panqu Wang
8. Pengfei Chen

Citations in the corpus

• Bottom-up Instance Segmentation using Deep Higher-Order CRFs (2016, methodology): “This CRF is fully differentiable and can be inserted as a layer of a neural network [2, 38].”
• Understanding Convolution for Semantic Segmentation (2017, methodology): “For example, for kernel size K = 3, an r = [1, 2, 5] pattern works as M2 = 2; however, an r = [1, 2, 9] pattern does not work as M2 = 5.”
• Fast Semantic Image Segmentation with High Order Context and Guided Filtering (2016, methodology): “In our formulation, as done in [16] and [15], we introduce L hidden”