Semantic labeling for prosthetic vision

The pascal visual object classes (VOC) challenge

Everingham, M., Van Gool, L., Williams, C. K. I., Winn, J., & Zisserman, A. (2010) · International Journal of Computer Vision · doi:10.1007/s11263-009-0275-4 · Cited by 19,599 · see citing works

Advances in Neural Information Processing Systems 19

(2007) · The MIT Press eBooks · doi:10.52202/085713 · Cited by 16,037 · see citing works

Are we ready for autonomous driving? The KITTI vision benchmark suite

Geiger, A., Lenz, P., & Urtasun, R. (2012) · 2012 IEEE Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2012.6248074 · Cited by 14,897 · see citing works

Proceedings of IEEE Conference on Computer Vision and Pattern Recognition

(1993) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.1993.341010 · Cited by 14,474 · see citing works

Proceedings of IEEE International Conference on Computer Vision

(1995) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.1995.466933 · Cited by 13,117 · see citing works

Advances in Neural Information Processing Systems 25

Zhang, Y., Sutton, C. A., Storkey, A., & Zoubin Ghahramani, A. (2012) · Cited by 12,653 · see citing works

Vision meets robotics: The KITTI dataset

Geiger, A., Lenz, P., Stiller, C., & Urtasun, R. (2013) · The International Journal of Robotics Research · doi:10.1177/0278364913491297 · Cited by 9,913 · see citing works

Proceedings European Conference on Computer Vision 2002

Heyden, A., Sparr, G., Nielsen, M., & Johansen, P. (2002) · Lund University Publications (Lund University) · Cited by 5,153 · see citing works

Efficient Inference in Fully Connected CRFs with Gaussian Edge Potentials

Krähenbühl, P., & Koltun, V. (2012) · arXiv · doi:10.48550/arxiv.1210.5644 · Cited by 2,908 · see citing works

2013 IEEE Conference on Computer Vision and Pattern Recognition

(2013) · doi:10.1109/cvpr19808.2013 · Cited by 2,439 · see citing works

Advances in Neural Information Processing Systems 21

Griffiths, T. L., Lucas, C. G., Williams, J. J., & Kalish, M. L. (2009) · neural information processing systems · Cited by 1,854 · see citing works

Scalable Nearest Neighbor Algorithms for High Dimensional Data

Muja, M., & Lowe, D. G. (2014) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2014.2321376 · Cited by 1,401 · see citing works

Semantic object classes in video: A high-definition ground truth database

Brostow, G., Fauqueur, J., & Cipolla, R. (2008) · Pattern Recognition Letters · doi:10.1016/j.patrec.2008.04.005 · Cited by 1,400 · see citing works

The sensations produced by electrical stimulation of the visual cortex

Brindley, G. S., & Lewin, W. S. (1968) · The Journal of Physiology · doi:10.1113/jphysiol.1968.sp008519 · Cited by 1,170 · see citing works

TextonBoost: Joint Appearance, Shape and Context Modeling for Multi-class Object Recognition and Segmentation

Shotton, J., Winn, J. M., Rother, C., & Criminisi, A. (2006) · Lecture notes in computer science · doi:10.1007/11744023_1 · Cited by 1,154 · see citing works

Segmentation and Recognition Using Structure from Motion Point Clouds

Brostow, G. J., Shotton, J., Fauqueur, J., & Cipolla, R. (2008) · Lecture Notes in Computer Science · doi:10.1007/978-3-540-88682-2_5 · Cited by 1,050 · see citing works

TextonBoost for Image Understanding: Multi-Class Object Recognition and Segmentation by Jointly Modeling Texture, Layout, and Context

Shotton, J., Winn, J. M., Rother, C., & Criminisi, A. (2007) · International Journal of Computer Vision · doi:10.1007/s11263-007-0109-1 · Cited by 1,014 · see citing works

Fast Edge Detection Using Structured Forests

Dollár, P., & Zitnick, C. L. (2014) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2014.2377715 · Cited by 965 · see citing works

A linear time algorithm for computing exact Euclidean distance transforms of binary images in arbitrary dimensions

Maurer, C. R., Qi, R., & Raghavan, V. (2003) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2003.1177156 · Cited by 911 · see citing works

Structured Forests for Fast Edge Detection

Dollár, P., & Zitnick, C. L. (2013) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2013.231 · Cited by 899 · see citing works

Visual perception in a blind subject with a chronic microelectronic retinal prosthesis

Humayun, M. S., Weiland, J. D., Fujii, G. Y., Greenberg, R., Williamson, R., Little, J., Mech, B., Cimmarusti, V., Van Boemel, G., Dagnelie, G., et al. (2003) · Vision Research · doi:10.1016/s0042-6989(03)00457-7 · Cited by 856 · see citing works

Multiscale conditional random fields for image labeling

He, X., Zemel, R. S., & Carreira-Perpiñán, M. Á. (2004) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2004.1315232 · Cited by 843 · see citing works

Subretinal electronic chips allow blind patients to read letters and combine them to words

Zrenner, E., Bartz-Schmidt, K. U., Benav, H., Besch, D., Bruckmann, A., Gabel, V.-P., Gekeler, F., Greppmaier, U., Harscher, A., Kibbel, S., et al. (2011) · Proceedings of the Royal Society B: Biological Sciences · doi:10.1098/rspb.2010.1747 · Cited by 819 · see citing works

Interim results from the international trial of Second Sight's visual prosthesis

Humayun, M. S., Dorn, J. D., da Cruz, L., Dagnelie, G., Sahel, J.-A., Stanga, P. E., Cideciyan, A. V., Duncan, J. L., Eliott, D., Filley, E., et al. (2012) · Ophthalmology · doi:10.1016/j.ophtha.2011.09.028 · Cited by 700 · see citing works

A new performance measure and evaluation benchmark for road detection algorithms

Fritsch, J., Kuhnl, T., & Geiger, A. (2013) · 16th International IEEE Conference on Intelligent Transportation Systems (ITSC 2013) · doi:10.1109/itsc.2013.6728473 · Cited by 690 · see citing works

Decomposing a scene into geometric and semantically consistent regions

Gould, S. J., Fulton, R., & Koller, D. (2009) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2009.5459211 · Cited by 687 · see citing works

Class segmentation and object localization with superpixel neighborhoods

Fulkerson, B., Vedaldi, A., & Soatto, S. (2009) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2009.5459175 · Cited by 648 · see citing works

Objects in Context

Rabinovich, A., Vedaldi, A., Galleguillos, C., Wiewiora, E., & Belongie, S. (2007) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2007.4408986 · Cited by 608 · see citing works

What is a good evaluation measure for semantic segmentation?

Csurka, G., Larlus, D., & Perronnin, F. (2013) · British Machine Vision Conference (BMVC) · doi:10.5244/c.27.32 · Cited by 536 · see citing works

SuperParsing: Scalable Nonparametric Image Parsing with Superpixels

Tighe, J., & Lazebnik, S. (2010) · Lecture notes in computer science · doi:10.1007/978-3-642-15555-0_26 · Cited by 481 · see citing works

Artificial vision with wirelessly powered subretinal electronic implant alpha-IMS

Stingl, K., Bartz-Schmidt, K. U., Besch, D., Braun, A., Bruckmann, A., Gekeler, F., Greppmaier, U., Hipp, S., Hörtdörfer, G., Kernstock, C., et al. (2013) · Proceedings of the Royal Society B: Biological Sciences · doi:10.1098/rspb.2013.0077 · Cited by 473 · see citing works

Object categorization using co-occurrence, location and appearance

Galleguillos, C., Rabinovich, A., & Belongie, S. (2008) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2008.4587799 · Cited by 467 · see citing works

Multi-Class Segmentation with Relative Location Prior

Gould, S. J., Rodgers, J., Cohen, D., Elidan, G., & Koller, D. (2008) · International Journal of Computer Vision · doi:10.1007/s11263-008-0140-x · Cited by 392 · see citing works

Nonparametric Scene Parsing via Label Transfer

Liu, C., Yuen, J., & Torralba, A. B. (2011) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2011.131 · Cited by 369 · see citing works

First-in-human trial of a novel suprachoroidal retinal prosthesis

Ayton, L. N., Blamey, P. J., Guymer, R. H., Luu, C. D., Nayagam, D. A. X., Sinclair, N. C., Shivdasani, M. N., Yeoh, J., McCombe, M. F., Briggs, R. J., et al. (2014) · PLoS ONE · doi:10.1371/journal.pone.0115239 · Cited by 333 · see citing works

British Machine Vision Conference, 2014

Crowley, E. J., & Zisserman, A. (2014) · Cited by 321 · see citing works

Social interactions: A first-person perspective

Fathi, A., Hodgins, J. K., & Rehg, J. M. (2012) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2012.6247805 · Cited by 298 · see citing works

First-Person Activity Recognition: What Are They Doing to Me?

Ryoo, M. S., & Matthies, L. H. (2013) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2013.352 · Cited by 283 · see citing works

Vision loss in Australia

Taylor, H. R., Keeffe, J. E., Vu, H. T., Wang, J. J., Rochtchina, E., Mitchell, P., & Pezzullo, M. L. (2005) · The Medical Journal of Australia · doi:10.5694/j.1326-5377.2005.tb06815.x · Cited by 225 · see citing works

Quality of Life of Low-Vision Patients and Outcomes of Low-Vision Rehabilitation

Stelmack, J. A. (2001) · Optometry and Vision Science · doi:10.1097/00006324-200105000-00017 · Cited by 214 · see citing works

Finding Things: Image Parsing with Regions and Per-Exemplar Detectors

Tighe, J., & Lazebnik, S. (2013) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2013.386 · Cited by 207 · see citing works

The functional performance of the Argus II retinal prosthesis

Stronks, H. C., & Dagnelie, G. (2014) · Expert Review of Medical Devices · doi:10.1586/17434440.2014.862494 · Cited by 189 · see citing works

Visual prostheses for the blind

Shepherd, R. K., Shivdasani, M. N., Nayagam, D. A. X., Williams, C. E., & Blamey, P. J. (2013) · Trends in biotechnology · doi:10.1016/j.tibtech.2013.07.001 · Cited by 181 · see citing works

Visually Guided Performance of Simple Tasks Using Simulated Prosthetic Vision

Hayes, J. S., Yin, V. T., Piyathaisere, D. V., Weiland, J. D., Humayun, M. S., & Dagnelie, G. (2003) · Artificial Organs · doi:10.1046/j.1525-1594.2003.07309.x · Cited by 162 · see citing works

Prevalence and Causes of Low Vision and Blindness in an Urban Malay Population

Wong, T. Y. (2008) · Archives of Ophthalmology · doi:10.1001/archopht.126.8.1091 · Cited by 155 · see citing works

Scene Segmentation with CRFs Learned from Partially Labeled Images

Triggs, B., & Verbeek, J. J. (2007) · neural information processing systems · Cited by 142 · see citing works

Efficient inference for fully-connected CRFs with stationarity

Zhang, Y., & Chen, T. (2012) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2012.6247724 · Cited by 105 · see citing works

The Association for Research in Vision and Ophthalmology

Kronfeld, P. C. (1973) · American Journal of Ophthalmology · doi:10.1016/0002-9394(73)90179-7 · Cited by 102 · see citing works

Detecting Snap Points in Egocentric Video with a Web Photo Prior

Xiong, B., & Grauman, K. L. (2014) · Lecture notes in computer science · doi:10.1007/978-3-319-10602-1_19 · Cited by 82 · see citing works

Nonparametric image parsing using adaptive neighbor sets

Eigen, D., & Fergus, R. (2012) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2012.6248004 · Cited by 79 · see citing works

Random Field Model for Integration of Local Information and Global Information

Toyoda, T., & Hasegawa, O. (2008) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2008.105 · Cited by 77 · see citing works

Saliency-based image processing for retinal prostheses

Parikh, N., Itti, L., & Weiland, J. D. (2010) · Journal of Neural Engineering · doi:10.1088/1741-2560/7/1/016006 · Cited by 70 · see citing works

Visual acuity measurement of prosthetic vision: a virtual-reality simulation study

Chen, S. C., Hallum, L. E., Lovell, N. H., & Suaning, G. J. (2005) · Journal of Neural Engineering · doi:10.1088/1741-2560/2/1/015 · Cited by 63 · see citing works

DARWIN: a framework for machine learning and computer vision research and development

Gould, S. J. (2012) · Cited by 57 · see citing works

PatchMatchGraph: Building a Graph of Dense Patch Correspondences for Label Transfer

Gould, S. J., & Zhang, Y. (2012) · Lecture notes in computer science · doi:10.1007/978-3-642-33715-4_32 · Cited by 57 · see citing works

Mobility and low contrast trip hazard avoidance using augmented depth

McCarthy, C., Walker, J. G., Lieby, P., Scott, A., & Barnes, N. (2015) · Journal of Neural Engineering · doi:10.1088/1741-2560/12/1/016003 · Cited by 49 · see citing works

Scene Segmentation with CRFs Learned from Partially Labeled Images

Verbeek, J. J., & Triggs, W. (2007) · HAL · Cited by 44 · see citing works

Filter-Based Mean-Field Inference for Random Fields with Higher-Order Terms and Product Label-Spaces

Vineet, V., Warrell, J., & Torr, P. H. S. (2012) · Lecture notes in computer science · doi:10.1007/978-3-642-33715-4_3 · Cited by 43 · see citing works

Learning object relationships via graph-based context model

Myeong, H., Chang, J. Y., & Lee, K. M. (2012) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2012.6247995 · Cited by 39 · see citing works

Substituting depth for intensity and real-time phosphene rendering: Visual navigation under low vision conditions

Lieby, P., Barnes, N. M., McCarthy, C., Liu, N., Dennett, H., Walker, J. G., Botea, V., & Scott, A. F. (2011) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/iembs.2011.6091977 · Cited by 38 · see citing works

Ground surface segmentation for navigation with a low resolution visual prosthesis

McCarthy, C., Barnes, N., & Lieby, P. (2011) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/iembs.2011.6091105 · Cited by 33 · see citing works

Active MAP Inference in CRFs for Efficient Semantic Segmentation

Roig, G., Boix, X., de Nijs, R., Ramos, S., Kuhnlenz, K., & Gool, L. V. (2013) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2013.287 · Cited by 30 · see citing works

Transformative Reality: Improving bionic vision with robotic sensing

Lui, W. L. D., Browne, D., Kleeman, L., Drummond, T., & Li, W. H. (2012) · 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society · doi:10.1109/embc.2012.6345929 · Cited by 23 · see citing works

Multiclass pixel labeling with non-local matching constraints

Gould, S. J. (2012) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2012.6248002 · Cited by 19 · see citing works

A salient information processing system for bionic eye with application to obstacle avoidance

Stacey, A., Li, Y., & Barnes, N. (2011) · doi:10.1109/iembs.2011.6091267 · Cited by 17 · see citing works

(RF)^2 -- Random Forest Random Field

Payet, N., & Todorović, S. (2010) · Cited by 16 · see citing works

Multi-class segmentation for traffic scenarios at over 50 FPS

Costea, A. D., & Nedevschi, S. (2014) · IEEE Intelligent Vehicles Symposium · doi:10.1109/ivs.2014.6856594 · Cited by 13 · see citing works

Image segmentation for enhancing symbol recognition in prosthetic vision

Horne, L., Barnes, N. M., McCarthy, C. D., & He, X. (2012) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc.2012.6346544 · Cited by 11 · see citing works

An overview of vision processing in implantable prosthetic vision

Barnes, N. M. (2013) · Proceedings - International Conference on Image Processing · doi:10.1109/icip.2013.6738315 · Cited by 11 · see citing works

Enhancing object contrast using augmented depth improves mobility in patients implanted with a retinal prosthesis

Barnes, N. M., Scott, A. F., Stacey, A., McCarthy, C. D., Feng, D. D., Petoe, M. A., Ayton, L. N., Dengate, R., Guymer, R. H., & Walker, J. G. (2015) · Swinburne figshare (Swinburne University of Technology) · Cited by 8 · see citing works

Mobility Experiments With Simulated Vision and sensory substitution of Depth

Barnes, N. M., Lieby, P., Dennett, H., McCarthy, C. D., Liu, N., & Walker, J. G. (2011) · Swinburne figshare (Swinburne University of Technology) · Cited by 8 · see citing works

Expectations of a Visual Prosthesis: Perspectives From People With Impaired Vision

Keeffe, J. E., Francis, K., Luu, C. D., Barnes, N., Lamoureux, E. L., & Guymer, R. H. (2010) · Investigative Ophthalmology & Visual Science · Cited by 8 · see citing works

The role of vision processing in prosthetic vision

Barnes, N. M., He, X., McCarthy, C. D., Horne, L., Kim, J., Scott, A., & Lieby, P. (2012) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc.2012.6345930 · Cited by 8 · see citing works

An face-based visual fixation system for prosthetic vision

He, X., Kim, J., & Barnes, N. (2012) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc.2012.6346590 · Cited by 7 · see citing works

Vision Processing with Lanczos2 Improves Low Vision Test Results in Implanted Visual Prosthetic Patients

Barnes, N. M., Scott, A. F., Stacey, A., Lieby, P., McCarthy, C. D., Petoe, M. A., Ayton, L. N., Shivdasani, M. N., Sinclair, N. C., & Walker, J. G. (2014) · Swinburne figshare (Swinburne University of Technology) · Cited by 5 · see citing works

Efficient scene parsing by sampling unary potentials in a fully-connected CRF

Horne, L., Álvarez, J. M., Salzmann, M., & Barnes, N. M. (2015) · IEEE Intelligent Vehicles Symposium · doi:10.1109/ivs.2015.7225786 · Cited by 5 · see citing works

Exploiting Sparsity for Real Time Video Labelling

Horne, L., Álvarez, J. M., & Barnes, N. M. (2013) · IEEE International Conference on Computer Vision Workshops · doi:10.1109/iccvw.2013.87 · Cited by 5 · see citing works

A bi-modal visual representation can enhance orientation and mobility performance with less than 20 phosphenes

Feng, D. D., Walker, J. G., Barnes, N. M., & McCarthy, C. D. (2014) · Swinburne figshare (Swinburne University of Technology) · Cited by 4 · see citing works

Computer vision for assistive technologies

Leo, M., Medioni, G. G., Trivedi, M. M., Takeo Kanade, A., & Farinella, G. M. (2016) · Computer Vision and Image Understanding · doi:10.1016/j.cviu.2016.09.001 · Cited by 228 · see citing works

Unifying Terrain Awareness for the Visually Impaired through Real-Time Semantic Segmentation

Yang, K., Wang, K., Bergasa, L. M., Romera, E., Hu, W., Sun, D., Sun, J., Cheng, R., Chen, T., & López-Guillén, E. (2018) · Sensors · doi:10.3390/s18051506 · Cited by 114 · see citing works

How eye-catching are natural features when walking through a park? Eye-tracking responses to videos of walks

Amati, M., Parmehr, E. G., McCarthy, C. D., & Sita, J. C. (2018) · Urban forestry & urban greening · doi:10.1016/j.ufug.2017.12.013 · Cited by 109 · see citing works

Trans4Trans: Efficient Transformer for Transparent Object and Semantic Scene Segmentation in Real-World Navigation Assistance

Zhang, J., Yang, K., Constantinescu, A., Peng, K., Müller, K., & Stiefelhagen, R. (2022) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2022.3161141 · Cited by 96 · see citing works

Rapid Detection of Blind Roads and Crosswalks by Using a Lightweight Semantic Segmentation Network

Cao, Z., Xu, X., Hu, B., & Zhou, M. (2020) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2020.2989129 · Cited by 81 · see citing works

Harmonization of Outcomes and Vision Endpoints in Vision Restoration Trials: Recommendations from the International HOVER Taskforce

Ayton, L. N., Rizzo, J. F., Bailey, I. L., Colenbrander, A., Dagnelie, G., Geruschat, D. R., Hessburg, P. C., McCarthy, C. D., Petoe, M. A., Rubin, G. S., et al. (2020) · Translational Vision Science & Technology · doi:10.1167/tvst.9.8.25 · Cited by 75 · see citing works

Deep Learning–Based Scene Simplification for Bionic Vision

Han, N., Srivastava, S., Xu, A., Klein, D., & Beyeler, M. (2021) · Augmented Humans Conference 2021 · doi:10.1145/3458709.3458982 · Cited by 45 · see citing works

Towards a <i>Smart Bionic Eye</i> : AI-powered artificial vision for the treatment of incurable blindness

Beyeler, M., & Sanchez-Garcia, M. (2022) · Journal of Neural Engineering · doi:10.1088/1741-2552/aca69d · Cited by 34 · see citing works

The application of computer vision to visual prosthesis

Wang, J., Zhu, H., Liu, J., Li, H., Han, Y., Zhou, R., & Zhang, Y. (2021) · Artificial Organs · doi:10.1111/aor.14022 · Cited by 26 · see citing works

Intersection Perception Through Real-Time Semantic Segmentation to Assist Navigation of Visually Impaired Pedestrians

Yang, K., Cheng, R., Bergasa, L. M., Romera, E., Wang, K., & Long, N. (2018) · IEEE International Conference on Robotics and Biomimetics (ROBIO) · doi:10.1109/robio.2018.8665211 · Cited by 26 · see citing works

Depth and motion cues with phosphene patterns for prosthetic vision

Perez-Yus, A., Bermudez-Cameo, J., Guerrero, J. J., & Lopez-Nicolas, G. (2017) · 2017 IEEE International Conference on Computer Vision Workshops (ICCVW) · doi:10.1109/iccvw.2017.179 · Cited by 24 · see citing works

The Relative Importance of Depth Cues and Semantic Edges for Indoor Mobility Using Simulated Prosthetic Vision in Immersive Virtual Reality

Rasla, A., & Beyeler, M. (2022) · ACM Symposium on Virtual Reality Software and Technology (VRST) · doi:10.1145/3562939.3565620 · Cited by 22 · see citing works

Artificial intelligence techniques for retinal prostheses: a comprehensive review and future direction

Wang, C., Fang, C., Zou, Y., Yang, J., & Sawan, M. (2023) · Journal of Neural Engineering · doi:10.1088/1741-2552/acb295 · Cited by 19 · see citing works

Deep Learning–Based Perceptual Stimulus Encoder for Bionic Vision

Relic, L., Zhang, B., Tuan, Y.-L., & Beyeler, M. (2022) · Augmented Humans International Conference (AHs) · doi:10.1145/3519391.3524034 · Cited by 18 · see citing works

Ego-Semantic Labeling of Scene from Depth Image for Visually Impaired and Blind People

Zatout, C., Larabi, S., Ilyes, M., & Barnabe, S. A. E. (2019) · IEEE International Conference on Computer Vision Workshops · doi:10.1109/iccvw.2019.00538 · Cited by 15 · see citing works

Atmospheric Transmission and Thermal Inertia Induced Blind Road Segmentation with a Large-Scale Dataset TBRSD

Chen, J., & Bai, X. (2023) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv51070.2023.00103 · Cited by 11 · see citing works

Semantic perception of curbs beyond traversability for real-world navigation assistance systems

Yang, K., Bergasa, L. M., Romera, E., Sun, D., Wang, K., & Barea, R. (2018) · IEEE International Conference on Vehicular Electronics and Safety (ICVES) · doi:10.1109/icves.2018.8519526 · Cited by 11 · see citing works

Pre‐processing visual scenes for retinal prosthesis systems: A comprehensive review

Holiel, H. A., Fawzi, S. A., & Al‐Atabany, W. (2024) · Artificial Organs · doi:10.1111/aor.14824 · Cited by 9 · see citing works

Human-Computer Synergies in Prosthetic Interactions

Carroll, J. M., Lee, S., Reddie, M., Beck, J., & Rosson, M. B. (2020) · Interaction design & architecture(s)/ID&A Interaction design & architecture(s) · doi:10.55612/s-5002-044-002 · Cited by 9 · see citing works

Non-parametric scene parsing: Label transfer methods and datasets

Bhowmick, A., Saharia, S., & Hazarika, S. M. (2022) · Computer Vision and Image Understanding · doi:10.1016/j.cviu.2022.103418 · Cited by 6 · see citing works

RGB-D Computer Vision Techniques for Simulated Prosthetic Vision

Bermúdez-Cameo, J., Badías, A., Guerrero-Viu, M., Nicolás, G. L., & Guerrero, J. J. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-58838-4_47 · Cited by 5 · see citing works

Deep Learning--Based Scene Simplification for Bionic Vision

Han, N., Srivastava, S., Xu, A., Klein, D., & Beyeler, M. (2021) · arXiv · doi:10.48550/arxiv.2102.00297 · Cited by 4 · see citing works

Learning Scene Representations for Human-assistive Displays Using Self-attention Networks

Ruiz-Serra, J., White, J., Petrie, S., Kameneva, T., & McCarthy, C. D. (2024) · ACM Transactions on Multimedia Computing Communications and Applications · doi:10.1145/3650111 · Cited by 4 · see citing works

Bionic Vision as Neuroadaptive XR: Closed-Loop Perceptual Interfaces for Neurotechnology

Beyeler, M. J. (2025) · IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct) · doi:10.1109/ismar-adjunct68609.2025.00034 · Cited by 4 · see citing works

A Novel Low Power Method of Combining Saliency and Segmentation for Mobile Displays

Suh, S., Hong, S. M., Kim, Y., & Park, J. (2021) · Electronics · doi:10.3390/electronics10101200 · Cited by 3 · see citing works

RASPV: A Robotics Framework for Augmented Simulated Prosthetic Vision

Pérez-Yus, A., Santos-Villafranca, M., Tomas-Barba, J., Bermúdez-Cameo, J., Montano-Oliván, L., Nicolás, G. L., & Guerrero, J. J. (2024) · IEEE Access · doi:10.1109/access.2024.3357400 · Cited by 3 · see citing works

Scene Simplification for Simulated Prosthetic Vision with Improved Scene Understanding

Yang, S., Han, D., Wu, J., Chen, X., & Chung, Y. Y. (2024) · International Conference on Consumer Electronics · doi:10.1109/icce59016.2024.10444304 · Cited by 2 · see citing works

Comparison of 3D Point Cloud Processing and CNN Prediction Based on RGBD Images for Bionic-eye’s Navigation

Kuasakunrungroj, A., Kondo, T., Rujikietgumjorn, S., Kaneko, H., & Lie, W. (2019) · doi:10.1109/incit.2019.8912066 · Cited by 2 · see citing works

Deploying an Instance Segmentation Algorithm to Implement Social Distancing for Prosthetic Vision

Luca, D. D., Moccia, S., & Micera, S. (2022) · IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops) · doi:10.1109/percomworkshops53856.2022.9767213 · Cited by 2 · see citing works

Enhancing Autonomous And Battery Electric Vehicle Performance Using AI And ML Algorithms

Correa, B. A. (2023) · doi:10.53555/kuey.v29i4.6489

Deep Learning-Driven Navigation Aids for the Visually Impaired: A Systematic Review of Semantic Segmentation-Based Approaches

Padmavathy, B., & Singh, M. K. (2025) · International Conference on Applied Artificial Intelligence and Computing (ICAAIC) · doi:10.1109/icaaic64647.2025.11330620

Special Issue on Assistive Computer Vision and Robotics - ``Assistive Solutions for Mobility, Communication and HMI''

Farinella, G. M., Takeo Kanade, A., Leo, M., Medioni, G. G., & Trivedi, M. M. (2016) · Computer Vision and Image Understanding · doi:10.1016/j.cviu.2016.05.014 · Cited by 1 · see citing works

Semantic labelling to aid navigation in prosthetic vision

Horne, L., Álvarez, J. M., McCarthy, C. D., & Barnes, N. M. (2015) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc.2015.7319117 · Cited by 6 · see citing works

Semantic Labelling for Prosthetic Vision

Horne, L. (2019) · ANU Open Research (Australian National University) · doi:10.25911/5da440dd21825

Smart Saliency Detection for Prosthetic Vision

Khalifa, N., Al‐Atabany, W., & Selim, S. (2024) · Communications in computer and information science · doi:10.1007/978-3-031-55729-3_11 · Cited by 2 · see citing works

Smart Navigation for Visual Prostheses in Virtual Reality: An End-to-End Framework for Priority-Based Scene Translation and Path GuidancePreprint

Abdellatif, M., Elsharkawy, F. S., Qassem, N. H., Emara, T. M., Kotb, N., Rushdi, M., & Elnabawy, R. H. (2026) · arXiv (Cornell University) · doi:10.48550/arxiv.2610.05772