Dynamic-excitation-based steady-state non-line-of-sight imaging via multi-branch convolutional neural network
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Yanlong Cao | Yanpeng Cao | Jiangxin Yang | Wenbin Zhu | Jian Chen | Bowen Zhao | R. Liang | Hao Chen | Xin Li | Lingfeng Shen
[1] Prasanna Rangarajan,et al. Fast non-line-of-sight imaging with high-resolution and wide field of view using synthetic wavelength holography , 2021, Nature Communications.
[2] Qionghai Dai,et al. Dynamic non-line-of-sight imaging system based on the optimization of point spread functions. , 2021, Optics express.
[3] Jian-Wei Pan,et al. Non-Line-of-Sight Imaging with Picosecond Temporal Resolution. , 2021, Physical review letters.
[4] Feihu Xu,et al. Compressed sensing for active non-line-of-sight imaging. , 2021, Optics express.
[5] Kiriakos N. Kutulakos,et al. Learned feature embeddings for non-line-of-sight imaging and recognition , 2020, ACM Trans. Graph..
[6] Andreas Velten,et al. Phasor field diffraction based reconstruction for fast non-line-of-sight imaging systems , 2020, Nature Communications.
[7] Jean-Yves Tourneret,et al. Seeing around corners with edge-resolved transient imaging , 2020, Nature Communications.
[8] Matthias B. Hullin,et al. Deep Non-Line-of-Sight Reconstruction , 2020, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[9] Felix Heide,et al. Deep-inverse correlography: towards real-time high-resolution non-line-of-sight imaging , 2020, Optica.
[10] Gregory W. Wornell,et al. Computational Mirrors: Blind Inverse Light Transport by Deep Matrix Factorization , 2019, NeurIPS.
[11] Aswin C. Sankaranarayanan,et al. Convolutional Approximations to the General Non-Line-of-Sight Imaging Operator , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).
[12] Christos Thrampoulidis,et al. Using Unknown Occluders to Recover Hidden Scenes , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[13] Charles Saunders,et al. Computational periscopy with an ordinary digital camera , 2019, Nature.
[14] Daniele Faccio,et al. Non-line-of-sight imaging , 2019, Nature Reviews Physics.
[15] Marc Alexa,et al. ABC: A Big CAD Model Dataset for Geometric Deep Learning , 2018, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[16] Felix Heide,et al. Steady-State Non-Line-Of-Sight Imaging , 2018, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[17] Gordon Wetzstein,et al. Confocal non-line-of-sight imaging based on the light-cone transform , 2018, Nature.
[18] Christos Thrampoulidis,et al. Revealing hidden scenes by photon-efficient occlusion-based opportunistic active imaging. , 2018, Optics express.
[19] Frédo Durand,et al. Turning Corners into Cameras: Principles and Methods , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).
[20] Daniel Buschek,et al. Neural network identification of people hidden from view with a single-pixel, single-photon detector , 2017, Scientific Reports.
[21] Ramesh Raskar,et al. Object classification through scattering media with deep learning on time resolved measurement. , 2017, Optics express.
[22] Jaime Martín,et al. Tracking objects outside the line of sight using 2D intensity images , 2016, Scientific Reports.
[23] Robert Henderson,et al. Detection and tracking of moving objects hidden from view , 2015, Nature Photonics.
[24] K. Eliceiri,et al. Non-line-of-sight imaging using a time-gated single photon avalanche diode. , 2015, Optics express.
[25] Jianxiong Xiao,et al. 3D ShapeNets: A deep representation for volumetric shapes , 2014, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[26] M. Fink,et al. Non-invasive single-shot imaging through scattering layers and around corners via speckle correlations , 2014, Nature Photonics.
[27] R. Raskar,et al. Recovering three-dimensional shape around a corner using ultrafast time-of-flight imaging , 2012, Nature Communications.
[28] Ramesh Raskar,et al. Looking around the corner using transient imaging , 2009, 2009 IEEE 12th International Conference on Computer Vision.
[29] James Davis,et al. 5d time-light transport matrix: What can we reason about scene properties? , 2008 .