Anurag Arnab.
Pixel-level Scene Understanding with Deep Structured Models.
PhD Thesis, University of Oxford , 2019
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Anurag Arnab*, Carl Doersch*, Andrew Zisserman.
Exploiting temporal context for 3D human pose estimation in the wild.
Computer Vision and Pattern Recognition (CVPR), 2019
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[Poster]
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Li Zhang*, Xiangtai Li*, Anurag Arnab, Kuiyuan Yang, Yunhai Tong, Philip H.S. Torr.
Dual Graph Convolutional Network for Semantic Segmentation.
British Machine Vision Conference (BMVC), 2019
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Harkirat Singh Behl, Mohammad Najafi, Anurag Arnab, Philip H.S. Torr.
Meta-Learning Deep Visual Words for Fast Video Object Segmentation.
NeurIPS Machine Learning for Autonomous Driving Workshop, 2019
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Qizhu Li*, Anurag Arnab*, Philip H.S Torr. Weakly- and Semi-Supervised Panoptic Segmentation.
European Conference on Computer Vision (ECCV), 2018
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Anurag Arnab, Ondrej Miksik, Philip H.S Torr. On the Robustness of Semantic Segmentation Models to
Adversarial Attacks. Computer Vision and Pattern Recognition (CVPR), 2018
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Anurag Arnab, Shuai Zheng, Sadeep Jayasumana, Bernardino Romera-Paredes, Måns Larsson, Alexander
Kirillov, Bogdan Savchynskyy, Carsten Rother, Fredrik Kahl, Philip H.S. Torr. Conditional Random Fields
Meet Deep Neural Networks for Semantic Segmentation. IEEE Signal Processing Magazine, 2018
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[Publisher]
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Måns Larsson, Anurag Arnab, Shuai Zheng, Philip H.S. Torr, Fredrik Kahl. Revisiting Deep Structured
Models for Pixel-Level Labeling with Gradient-Based Inference. SIAM Journal on Imaging Sciences,
2018
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Anurag Arnab, Philip H.S Torr. Pixelwise Instance Segmentation with a Dynamically Instantiated
Network. Computer Vision and Pattern Recognition (CVPR), 2017
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Qizhu Li*, Anurag Arnab*, Philip H.S Torr. Holistic, Instance-level Human Parsing. British
Machine Vision Conference (BMVC), 2017
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Måns Larsson, Anurag Arnab, Fredrik Kahl, Shuai Zheng, Philip H.S. Torr. A Projected Gradient
Descent Method for CRF Inference allowing End-To-End Training of Arbitrary Pairwise Potentials.
Energy Minimization Methods in Computer Vision and Pattern Recognition (EMMCVPR), 2017
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Anurag Arnab, Sadeep Jayasumana, Shuai Zheng, Philip H.S Torr. Higher Order Conditional Random
Fields in Deep Neural Networks. European Conference on Computer Vision (ECCV), 2016
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Anurag Arnab, Philip H.S Torr. Bottom-up Instance Segmentation using Deep Higher-Order CRFs
British Machine Vision Conference (BMVC), 2016
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Anurag Arnab, Michael Sapienza, Stuart Golodetz, Julien Valentin, Ondrej Miksik, Shahram Izadi,
Philip H.S. Torr.
Joint Object-Material Category Segmentation from Audio-Visual Cues British Machine Vision Conference
(BMVC), 2015
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[Dataset]
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Stuart Golodetz, Michael Sapienza, Julien Valentin, Vibhav Vineet, Ming-Ming Cheng, Anurag Arnab,
Victor Adrian Prisacariu, Olaf Kaehler, Carl Yuheng Ren, David W. Murray, Shahram Izadi, Philip H.S.
Torr.
SemanticPaint: A Framework for the Interactive Segmentation of 3D Scenes arXiv 1510.03727, 2015
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Stuart Golodetz, Michael Sapienza, Julien Valentin, Vibhav Vineet, Ming-Ming Cheng, Victor Adrian
Prisacariu, Olaf Kaehler, Carl Yuheng Ren, Anurag Arnab, Stephen Hicks, David W. Murray, Shahram
Izadi, Philip H.S. Torr.
SemanticPaint: Interactive Segmentation and Learning of 3D Worlds ACM SIGGRAPH 2015 Emerging
Technologies, 2015 (live demo)
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Scene Understanding with Deep Structured Models
Invited talk at University of Warsaw. January 2020
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Learning from Weak Supervision: Panoptic Segmentation and 3D Human Pose Estimation
Invited talk at Learning from Imperfect Data Workshop at Computer Vision and Pattern Recognition (CVPR), June 2019
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Pixelwise Instance Segmentation with a Dynamically Instantiated Network
ETH Zurich, August 2017
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Holistic Scene Understanding with Deep Learning and Dense Random Fields
Invited Tutorial at Deep
Learning Meets Model Optimization and Statistical Inference at European Conference on Computer
Vision (ECCV), October 2016.
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Joint Object-Material Category Segmentation from Audio-Visual Cues
Vision and Learning Seminar (Online), February 2016
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Joint Object-Material Category Segmentation from Audio-Visual Cues
CVSSP Seminar, University of Surrey, November 2015
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