Joint depth map super-resolution method via deep hybrid-cross guidance filter

[1]  Wenqi Ren,et al.  Memory-Augmented Deep Unfolding Network for Guided Image Super-resolution , 2022, International Journal of Computer Vision.

[2]  Jixin Liu,et al.  Multi-attention augmented network for single image super-resolution , 2022, Pattern Recognit..

[3]  Sam Kwong,et al.  BridgeNet: A Joint Learning Network of Depth Map Super-Resolution and Monocular Depth Estimation , 2021, ACM Multimedia.

[4]  Jiangshe Zhang,et al.  Discrete Cosine Transform Network for Guided Depth Map Super-Resolution , 2021, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[5]  Chunjie Zhang,et al.  Towards Fast and Accurate Real-World Depth Super-Resolution: Benchmark Dataset and Baseline , 2021, 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[6]  Debin Zhao,et al.  High-resolution Depth Maps Imaging via Attention-based Hierarchical Multi-modal Fusion , 2021, IEEE Transactions on Image Processing.

[7]  Haojie Li,et al.  Learning Scene Structure Guidance via Cross-Task Knowledge Transfer for Single Depth Super-Resolution , 2021, 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[8]  Zhongyu Jiang,et al.  Deep edge map guided depth super resolution , 2021, Signal Process. Image Commun..

[9]  Yong Yang,et al.  Depth Map Enhancement by Revisiting Multi-Scale Intensity Guidance Within Coarse-to-Fine Stages , 2020, IEEE Transactions on Circuits and Systems for Video Technology.

[10]  Junjun Jiang,et al.  Hierarchical dense recursive network for image super-resolution , 2020, Pattern Recognit..

[11]  Xiying Li,et al.  Towards Lighter and Faster: Learning Wavelets Progressively for Image Super-Resolution , 2020, ACM Multimedia.

[12]  Rui Xu,et al.  Depth upsampling based on deep edge-aware learning , 2020, Pattern Recognit..

[13]  Baopu Li,et al.  PMBANet: Progressive Multi-Branch Aggregation Network for Scene Depth Super-Resolution , 2020, IEEE Transactions on Image Processing.

[14]  Jin Wang,et al.  Multi-Direction Dictionary Learning Based Depth Map Super-Resolution With Autoregressive Modeling , 2020, IEEE Transactions on Multimedia.

[15]  Qionghai Dai,et al.  Color-Guided Depth Image Recovery With Adaptive Data Fidelity and Transferred Graph Laplacian Regularization , 2020, IEEE Transactions on Circuits and Systems for Video Technology.

[16]  Zhifeng Chen,et al.  Multi-Scale Frequency Reconstruction for Guided Depth Map Super-Resolution via Deep Residual Network , 2020, IEEE Transactions on Circuits and Systems for Video Technology.

[17]  Jean Ponce,et al.  Deformable Kernel Networks for Joint Image Filtering , 2019, International Journal of Computer Vision.

[18]  Pier Luigi Dragotti,et al.  Deep Convolutional Neural Network for Multi-Modal Image Restoration and Fusion , 2019, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[19]  Jianjia Zhang,et al.  Pyramid-Structured Depth MAP Super-Resolution Based on Deep Dense-Residual Network , 2019, IEEE Signal Processing Letters.

[20]  Yuming Fang,et al.  Residual dense network for intensity-guided depth map enhancement , 2019, Inf. Sci..

[21]  Vishal M. Patel,et al.  HA-CCN: Hierarchical Attention-Based Crowd Counting Network , 2019, IEEE Transactions on Image Processing.

[22]  Guoping Qiu,et al.  Side Window Filtering , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[23]  Hang Su,et al.  Pixel-Adaptive Convolutional Neural Networks , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[24]  Wen Gao,et al.  Depth Super-Resolution via Joint Color-Guided Internal and External Regularizations , 2019, IEEE Transactions on Image Processing.

[25]  Wei Wu,et al.  Feedback Network for Image Super-Resolution , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[26]  Ping Li,et al.  Deep Color Guided Coarse-to-Fine Convolutional Network Cascade for Depth Image Super-Resolution , 2019, IEEE Transactions on Image Processing.

[27]  In-So Kweon,et al.  CBAM: Convolutional Block Attention Module , 2018, ECCV.

[28]  Qiang Wu,et al.  Minimum Spanning Forest With Embedded Edge Inconsistency Measurement Model for Guided Depth Map Enhancement , 2018, IEEE Transactions on Image Processing.

[29]  Haojie Li,et al.  Depth Super-Resolution with Deep Edge-Inference Network and Edge-Guided Depth Filling , 2018, 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

[30]  Gregory Shakhnarovich,et al.  Deep Back-Projection Networks for Super-Resolution , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.

[31]  Qiang Wu,et al.  Explicit Edge Inconsistency Evaluation Model for Color-Guided Depth Map Enhancement , 2018, IEEE Transactions on Circuits and Systems for Video Technology.

[32]  Jean Ponce,et al.  Robust Guided Image Filtering Using Nonconvex Potentials , 2018, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[33]  Narendra Ahuja,et al.  Joint Image Filtering with Deep Convolutional Networks , 2017, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[34]  Yao Zhao,et al.  Single depth image super-resolution with multiple residual dictionary learning and refinement , 2017, 2017 IEEE International Conference on Multimedia and Expo (ICME).

[35]  Narendra Ahuja,et al.  Deep Joint Image Filtering , 2016, ECCV.

[36]  Xiaoou Tang,et al.  Depth Map Super-Resolution by Deep Multi-Scale Guidance , 2016, ECCV.

[37]  Jonathan T. Barron,et al.  The Fast Bilateral Solver , 2015, ECCV.

[38]  Xi Wang,et al.  High-Resolution Stereo Datasets with Subpixel-Accurate Ground Truth , 2014, GCPR.

[39]  Rogério Schmidt Feris,et al.  Single depth image super resolution and denoising via coupled dictionary learning with local constraints and shock filtering , 2014, 2014 IEEE International Conference on Multimedia and Expo (ICME).

[40]  Feng Liu,et al.  Depth Enhancement via Low-Rank Matrix Completion , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.

[41]  Horst Bischof,et al.  Image Guided Depth Upsampling Using Anisotropic Total Generalized Variation , 2013, 2013 IEEE International Conference on Computer Vision.

[42]  Ming-Yu Liu,et al.  Joint Geodesic Upsampling of Depth Images , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.

[43]  Gabriel J. Brostow,et al.  Patch Based Synthesis for Single Depth Image Super-Resolution , 2012, ECCV.

[44]  Derek Hoiem,et al.  Indoor Segmentation and Support Inference from RGBD Images , 2012, ECCV.

[45]  Minh N. Do,et al.  Cross-based local multipoint filtering , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.

[46]  Michael S. Brown,et al.  High quality depth map upsampling for 3D-TOF cameras , 2011, 2011 International Conference on Computer Vision.

[47]  Jian Sun,et al.  Guided Image Filtering , 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[48]  A. Lakshmi,et al.  Gaussian Restoration pyramid : Application of image restoration to Laplacian pyramid compression , 2010, 2010 IEEE 2nd International Advance Computing Conference (IACC).

[49]  Dani Lischinski,et al.  Joint bilateral upsampling , 2007, ACM Trans. Graph..

[50]  Christopher Joseph Pal,et al.  Learning Conditional Random Fields for Stereo , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.

[51]  Heiko Hirschmüller,et al.  Evaluation of Cost Functions for Stereo Matching , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.

[52]  Sebastian Thrun,et al.  An Application of Markov Random Fields to Range Sensing , 2005, NIPS.

[53]  D. Scharstein,et al.  A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms , 2001, Proceedings IEEE Workshop on Stereo and Multi-Baseline Vision (SMBV 2001).

[54]  Yuming Fang,et al.  MIG-Net: Multi-Scale Network Alternatively Guided by Intensity and Gradient Features for Depth Map Super-Resolution , 2022, IEEE Transactions on Multimedia.

[55]  Ping An,et al.  Frequency-Dependent Depth Map Enhancement via Iterative Depth-Guided Affine Transformation and Intensity-Guided Refinement , 2021, IEEE Transactions on Multimedia.

[56]  Pengfei Li,et al.  Image super-resolution via sparse representation and local texture constraint , 2017, 2017 12th IEEE Conference on Industrial Electronics and Applications (ICIEA).

[57]  Rogério Schmidt Feris,et al.  Edge-Guided Single Depth Image Super Resolution , 2016, IEEE Transactions on Image Processing.