Evaluating Bayesian Deep Learning Methods for Semantic Segmentation

Jishnu Mukhoti, Yarin Gal

Type: Preprint

Publication Date: 2018-01-01

Citations: 152

DOI: https://doi.org/10.48550/arxiv.1811.12709

View Publication

Locations

arXiv (Cornell University) - View
DataCite API - View

Similar Works

Action	Title	Year	Authors
+ PDF Chat	Bayesian SegNet: Model Uncertainty in Deep Convolutional Encoder-Decoder Architectures for Scene Understanding	2017	Alex Kendall Vijay Badrinarayanan Roberto Cipolla
+	Bayesian SegNet: Model Uncertainty in Deep Convolutional Encoder-Decoder Architectures for Scene Understanding	2017	Alex Kendall Vijay Badrinarayanan Roberto Cipolla
+	Bayesian SegNet: Model Uncertainty in Deep Convolutional Encoder-Decoder Architectures for Scene Understanding	2015	Alex Kendall Vijay Badrinarayanan Roberto Cipolla
+	Deep Deterministic Uncertainty for Semantic Segmentation	2021	Jishnu Mukhoti Joost van Amersfoort Philip H. S. Torr Yarin Gal
+	Pixel-wise Gradient Uncertainty for Convolutional Neural Networks applied to Out-of-Distribution Segmentation	2023	Kira Maag Tobias Riedlinger
+	Automated Detection of Label Errors in Semantic Segmentation Datasets via Deep Learning and Uncertainty Quantification	2022	Matthias Rottmann Marco Reese
+ PDF Chat	Automated Detection of Label Errors in Semantic Segmentation Datasets via Deep Learning and Uncertainty Quantification	2023	Matthias Rottmann Marco Reese
+	DUDES: Deep Uncertainty Distillation using Ensembles for Semantic Segmentation	2023	Steven Landgraf Kira Wursthorn Markus Hillemann Markus Ulrich
+	Evaluating Uncertainty Estimation Methods on 3D Semantic Segmentation of Point Clouds	2020	Swaroop Bhandary K Nico Hochgeschwender Paul G. Plöger Frank Kirchner Matías Valdenegro-Toro
+ PDF Chat	The Fishyscapes Benchmark: Measuring Blind Spots in Semantic Segmentation	2021	Hermann Blum Paul-Edouard Sarlin Juan Nieto Roland Siegwart César Cadena
+ PDF Chat	A Review of Bayesian Uncertainty Quantification in Deep Probabilistic Image Segmentation	2024	M. M. A. Valiuddin Ruud J. G. van Sloun C. G. A. Viviers P. H. N. de With Fons van der Sommen
+ PDF Chat	Uncertainty Quantification for Bird's Eye View Semantic Segmentation: Methods and Benchmarks	2024	Linlin Yu Bowen Yang Tianhao Wang Kangshuo Li Feng Chen
+	U-CE: Uncertainty-aware Cross-Entropy for Semantic Segmentation	2023	Steven Landgraf Markus Hillemann Kira Wursthorn Markus Ulrich
+	Efficient Uncertainty Estimation for Semantic Segmentation in Videos	2018	Po‐Yu Huang Wan‐Ting Hsu Chun-Yueh Chiu Tingfan Wu Min Sun
+	Make Me a BNN: A Simple Strategy for Estimating Bayesian Uncertainty from Pre-trained Models	2023	Gianni Franchi Olivier Laurent Maxence Leguéry Andrei Bursuc Andrea Pilzer Angela Yao
+	Weakly-Supervised Semantic Segmentation by Learning Label Uncertainty	2021	Robby Neven Davy Neven Bert De Brabandere Marc Proesmans Toon Goedemé
+	Weakly-Supervised Semantic Segmentation by Learning Label Uncertainty	2021	Robby Neven Davy Neven Bert De Brabandere Marc Proesmans Toon Goedemé
+	Quantifying Model Uncertainty for Semantic Segmentation using Operators in the RKHS	2022	Rishabh Singh José C. Prı́ncipe
+ PDF Chat	Weakly-Supervised Semantic Segmentation by Learning Label Uncertainty	2021	Robby Neven Davy Neven Bert De Brabandere Marc Proesmans Toon Goedemé
+	Reliability in Semantic Segmentation: Are We on the Right Track?	2023	Pau de Jorge Riccardo Volpi Philip Torr Grégory Rogez

Works That Cite This (92)

Action	Title	Year	Authors
+	Consensus Synergizes with Memory: A Simple Approach for Anomaly Segmentation in Urban Scenes	2021	Jiazhong Cen Zenkun Jiang Lingxi Xie Qi Tian Xiaokang Yang Wei Shen
+ PDF Chat	A survey on epistemic (model) uncertainty in supervised learning: Recent advances and applications	2021	Xinlei Zhou Han Liu Farhad Pourpanah Tieyong Zeng Xizhao Wang
+ PDF Chat	Uncertainty-Guided Boundary Learning for Imbalanced Social Event Detection	2023	Jiaqian Ren Hao Peng Lei Jiang Zhiwei Liu Jia Wu Zhengtao Yu Philip S. Yu
+	Improving Uncertainty-Error Correspondence in Deep Bayesian Medical Image Segmentation	2023	Prerak Mody
+	Improving Uncertainty-Error Correspondence in Deep Bayesian Medical Image Segmentation	2023	Prerak Mody
+	Hyperbolic Audio Source Separation	2023	Darius Petermann Gordon Wichern Aswin Shanmugam Subramanian Jonathan Le Roux
+ PDF Chat	MonoLoco: Monocular 3D Pedestrian Localization and Uncertainty Estimation	2019	Lorenzo Bertoni S. Kreiss Alexandre Alahi
+ PDF Chat	QU-BraTS: MICCAI BraTS 2020 Challenge on Quantifying Uncertainty in Brain Tumor Segmentation – Analysis of Ranking Scores and Benchmarking Results	2022	Raghav Mehta Angelos Filos Ujjwal Baid Chiharu Sako Richard McKinley Michael Rebsamen Katrin Dätwyler Raphael Meier Piotr Radojewski Gowtham Krishnan Murugesan
+ PDF Chat	Calibrated Adversarial Refinement for Stochastic Semantic Segmentation	2021	Elias Kassapis Georgi Dikov Deepak Gupta Cedric Nugteren
+	Dense Uncertainty Estimation	2021	Jing Zhang Yuchao Dai Mochu Xiang Deng-Ping Fan Peyman Moghadam Mingyi He Christian Walder Kaihao Zhang Mehrtash Harandi Nick Barnes

Works Cited by This (35)

Action	Title	Year	Authors
+	Deep Learning using Linear Support Vector Machines	2013	Yichuan Tang
+	An Empirical Evaluation of Deep Learning on Highway Driving	2015	Brody Huval Tao Wang Sameep Tandon Jeff Kiske Will Song Joel Pazhayampallil Mykhaylo Andriluka Pranav Rajpurkar Toki Migimatsu Royce Cheng-Yue
+	Very Deep Convolutional Networks for Large-Scale Image Recognition	2014	Karen Simonyan Andrew Zisserman
+	Generating Sequences With Recurrent Neural Networks	2013	Alex Graves
+ PDF Chat	Fully convolutional networks for semantic segmentation	2015	Jonathan Long Evan Shelhamer Trevor Darrell
+ PDF Chat	Fast image scanning with deep max-pooling convolutional neural networks	2013	Alessandro Giusti Dan Cireşan Jonathan Masci Luca Maria Gambardella Jürgen Schmidhuber
+ PDF Chat	Going deeper with convolutions	2015	Christian Szegedy Wei Liu Yangqing Jia Pierre Sermanet Scott Reed Dragomir Anguelov Dumitru Erhan Vincent Vanhoucke Andrew Rabinovich
+	Bayesian SegNet: Model Uncertainty in Deep Convolutional Encoder-Decoder Architectures for Scene Understanding	2017	Alex Kendall Vijay Badrinarayanan Roberto Cipolla
+	Bayesian Learning via Stochastic Gradient Langevin Dynamics	2011	Max Welling Yee Whye Teh
+	Deep Speech 2: End-to-End Speech Recognition in English and Mandarin	2015	Dario Amodei Rishita Anubhai Eric Battenberg Carl Case Jared Casper Bryan Catanzaro Jingdong Chen Mike Chrzanowski Adam Coates Greg Diamos