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Self-supervised Neural Audio-Visual Sound Source Localization via Probabilistic Spatial Modeling [article]

Yoshiki Masuyama, Yoshiaki Bando, Kohei Yatabe, Yoko Sasaki, Masaki Onishi, Yasuhiro Oikawa
2020 arXiv   pre-print
These DNNs are jointly trained in a self-supervised manner based on a probabilistic spatial audio model.  ...  Our system for localizing sound source objects in the image is composed of audio and visual DNNs. The visual DNN is trained to localize sound source candidates within an input image.  ...  Fig. 4 : 4 Overview of our self-supervised training based on probabilistic spatial audio model. The green and blue blocks are the visual and audio DNNs, respectively.  ... 
arXiv:2007.13976v1 fatcat:k4sho4ggnbafbfc3wyhngmg76a

Towards training-free appearance-based localization: Probabilistic models for whole-image descriptors

Stephanie M. Lowry, Gordon F. Wyeth, Michael J. Milford
2014 2014 IEEE International Conference on Robotics and Automation (ICRA)  
In FAB-MAP [4] , a state of the art probabilistic visual mapping system, local features are combined with a visual bag-of-words [9, 10] and the robot location can be calculated based on the joint probability  ...  We demonstrate the effectiveness of the whole-image probability model using CAT-Graph [5, 16] , an appearance-based localization system originally designed for a FAB-MAP-like [4] probabilistic visual  ... 
doi:10.1109/icra.2014.6906932 dblp:conf/icra/LowryWM14 fatcat:jjwhuhixyna2jmfbsz5noort24

Probabilistic Learning by Rodent Grid Cells

Allen Cheung, Daniel Bush
2016 PLoS Computational Biology  
Hence, grid cells may provide the universal metric upon which spatial cognition is based.  ...  a probabilistic learning process.  ...  Predictive short-range boundary vector maps were produced to visualize the learned local boundary direction (S1.3.9 Text).  ... 
doi:10.1371/journal.pcbi.1005165 pmid:27792723 pmcid:PMC5085080 fatcat:wnhsi6a4g5h25ioq4fmwr5j6yy

Mapping a Suburb With a Single Camera Using a Biologically Inspired SLAM System

M.J. Milford, G.F. Wyeth
2008 IEEE Transactions on robotics  
This paper describes a biologically inspired approach to vision-only simultaneous localization and mapping (SLAM) on ground-based platforms.  ...  Index Terms-Bio-inspired robotics, monocular vision simultaneous localization and mapping (SLAM).  ...  Only during previously seen local view input is there any form of probabilistic representation, as multiple peaks caused by ambiguous visual scenes could be argued to represent multiple probabilistic beliefs  ... 
doi:10.1109/tro.2008.2004520 fatcat:za4rp73a5ncsdjl5ntxucaswgy

GPSlam: Marrying Sparse Geometric and Dense Probabilistic Visual Mapping

Katrin Pirker, Matthias Rüther, Gerald Schweighofer, Horst Bischof
2011 Procedings of the British Machine Vision Conference 2011  
We propose a novel, hybrid SLAM system to construct a dense occupancy grid map based on sparse visual features and dense depth information.  ...  We propose a novel map-update criterion to prevent inconsistencies, and a robust measure to discriminate exploration from localization.  ...  Sensor noise is handled by the probabilistic mapping routine, but error propagation in visual odometry is not.  ... 
doi:10.5244/c.25.115 dblp:conf/bmvc/PirkerRSB11 fatcat:ta4wr3h3pbcsfink3hseyaubla

Lost! Leveraging the Crowd for Probabilistic Visual Self-Localization

Marcus A. Brubaker, Andreas Geiger, Raquel Urtasun
2013 2013 IEEE Conference on Computer Vision and Pattern Recognition  
By exploiting freely available, community developed maps and visual odometry measurements, we are able to localize a vehicle up to 3m after only a few seconds of driving on maps which contain more than  ...  Because of the probabilistic nature of the model we are able to cope with uncertainty due to noisy visual odometry and inherent ambiguities in the map (e.g., in a Manhattan world).  ...  Visual Self-Localization: We demonstrate localizing a vehicle with an average accuracy of 3.1m within a map of ∼ 2, 150km of road using only visual odometry measurements and freely available maps.  ... 
doi:10.1109/cvpr.2013.393 dblp:conf/cvpr/BrubakerGU13 fatcat:ffvd4nnm6vbjvdeaoxznre6umi

Exploiting Sparse Semantic HD Maps for Self-Driving Vehicle Localization [article]

Wei-Chiu Ma, Ignacio Tartavull, Ioan Andrei Bârsan, Shenlong Wang, Min Bai, Gellert Mattyus, Namdar Homayounfar, Shrinidhi Kowshika Lakshmikanth, Andrei Pokrovsky, Raquel Urtasun
2019 arXiv   pre-print
Our approach does not require detailed knowledge about the appearance of the world, and our maps require orders of magnitude less storage than maps utilized by traditional geometry- and LiDAR intensity-based  ...  localizers.  ...  In order to be able to exploit HD maps, self-driving cars have to localize themselves with respect to the map.  ... 
arXiv:1908.03274v1 fatcat:gdbrztrdlnebtmbqp364hopiky

Probabilistic Self-Organizing Maps for Text-Independent Speaker Identification

Ayoub Bouziane, Jamal Kharroubi, Arsalane Zarghili
2018 TELKOMNIKA (Telecommunication Computing Electronics and Control)  
self-organizing maps.  ...  The present paper introduces a novel speaker modeling technique for text-independent speaker identification using probabilistic self-organizing maps (PbSOMs).  ...  In the same perspective, the probabilistic self-organizing maps method [4] - [6] , based on the combination between the strengths of self-organizing maps and mixture models, was proposed and yielded  ... 
doi:10.12928/telkomnika.v16i1.7559 fatcat:by4vvjtxlrgk3lfyc4ce6wwl6e

Connectivity of the Cingulate Sulcus Visual Area (CSv) in the Human Cerebral Cortex

Andrew T. Smith, Anton L. Beer, Michele Furlan, Rogier B. Mars
2017 Cerebral Cortex  
The human cingulate sulcus visual area (CSv) responds selectively to visual and vestibular cues to self-motion.  ...  Although it is more selective for visual self-motion cues than any other brain region studied, it is not known whether CSv mediates perception of self-motion.  ...  The parietal ROIs were based on the probabilistic atlas of Mars et al (2011) .  ... 
doi:10.1093/cercor/bhx002 pmid:28108496 fatcat:bm6ay3vf4ffgzgrr7tu3avosji

3DTV - Panoramic 3D Model Acquisition and its 3D Visualization on the Interactive Fogscreen

Sven Fleck, Florian Busch, Peter Biber, Wolfgang Straber, Ismo Rakkolainen, Stephen DiVerdi, Tobias Hollerer
2006 2006 International Conference on Image Processing  
Future 3D Television critically relies on mechanisms for automatically acquiring and visualizing high quality 3D content of both indoor and outdoor scenes.  ...  We present both the 3D acquisition and semi-immersive 3D visualization to give an impression how a future 3D Television system could be like.  ...  MAP BUILDING & LOCALIZATION BY PROBABILISTIC SCAN MATCHING We use a probabilistic scan matching approach to solve the simultaneous localization and mapping (SLAM) problem based on LI.  ... 
doi:10.1109/icip.2006.312965 dblp:conf/icip/FleckBBSRDH06 fatcat:hf677ustyjc4toncxe45np5xha

A probabilistic Self-Organizing Map for facial recognition

Gregoire Lefebvre, Christophe Garcia
2008 Pattern Recognition (ICPR), Proceedings of the International Conference on  
In this paper, we propose to label a Self-Organizing Map (SOM) to measure image similarity.  ...  Facial recognition is then performed by a probabilistic decision rule.  ...  This large amount of training information is then organized thanks to a Self Organizing Map [8] .  ... 
doi:10.1109/icpr.2008.4760955 dblp:conf/icpr/LefebvreG08 fatcat:mpqfmfmwfzdppdcbl32calds3e

FreMEn: Frequency Map Enhancement for Long-Term Mobile Robot Autonomy in Changing Environments

Tomas Krajnik, Jaime P. Fentanes, Joao M. Santos, Tom Duckett
2017 IEEE Transactions on robotics  
Rather than using a fixed probability value, the method models the uncertainty of the elementary environment states by probabilistic functions of time.  ...  In a series of experiments performed over periods of days to years, we demonstrate that the proposed approach improves localization, path planning and exploration.  ...  FREMEN FOR VISUAL LOCALIZATION To evaluate the usefulness of the approach, we apply it to the problem of visual-based localization in changing environments.  ... 
doi:10.1109/tro.2017.2665664 fatcat:7v4wunnbrjdcxb33hxgwirwfqm

A Colorization Algorithm with Artifacts Suppression on Real Time Video

2016 International Journal of Science and Research (IJSR)  
First, an iterative probabilistic color mapping is applied to construct the mapping relationship between the reference and target frames.  ...  In this paper, a color transfer approach with corruptive artifacts suppression is represent, which performs iterative probabilistic color mapping and this Paper extend the technique to colorize the videos  ...  It's well known that human visual system is more sensitive to local intensity differences than to intensity itself.  ... 
doi:10.21275/v5i4.nov162748 fatcat:y33ogp447nhltfm3c274hurxdm

Building Extraction from Remote Sensing Images with Sparse Token Transformers

Keyan Chen, Zhengxia Zou, Zhenwei Shi
2021 Remote Sensing  
Most building extraction methods are based on Convolutional Neural Networks (CNN).  ...  Visualization of the spatial probabilistic maps. The rows from top to bottom are the input image, the spatial probabilistic map, and the ground truth label, respectively.  ...  Spatial Token Probabilistic Maps In our method, the sparse tokens of the transformer input are directly sampled based on the token probabilistic maps.  ... 
doi:10.3390/rs13214441 fatcat:sbe72zybwrdw3anlg7kyeyzlve

TranSalNet: Towards perceptually relevant visual saliency prediction [article]

Jianxun Lou, Hanhe Lin, David Marshall, Dietmar Saupe, Hantao Liu
2022 arXiv   pre-print
This hinders CNN-based saliency models from capturing properties that emulate viewing behaviour of humans.  ...  Transformers have shown great potential in encoding long-range information by leveraging the self-attention mechanism.  ...  system is proficient in capturing both local and global/long-range visual information).  ... 
arXiv:2110.03593v2 fatcat:cufk3eznwrbulesngltefrkfky
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