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Gene Cheung
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2020 – today
- 2024
- [j81]Fei Chen, Gene Cheung, Xue Zhang:
Manifold Graph Signal Restoration Using Gradient Graph Laplacian Regularizer. IEEE Trans. Signal Process. 72: 744-761 (2024) - [j80]Saghar Bagheri, Tam Thuc Do, Gene Cheung, Antonio Ortega:
Spectral Graph Learning With Core Eigenvectors Prior via Iterative GLASSO and Projection. IEEE Trans. Signal Process. 72: 3958-3972 (2024) - [c188]Tam Thuc Do, Philip A. Chou, Gene Cheung:
Volumetric 3d Point Cloud Attribute Compression: Learned Polynomial Bilateral Filter for Prediction. ICASSP 2024: 3915-3919 - [c187]Niruhan Viswarupan, Gene Cheung, Fengbo Lan, Michael S. Brown:
Mixed Graph Signal Analysis of Joint Image Denoising / Interpolation. ICASSP 2024: 9431-9435 - [c186]Fei Chen, Gene Cheung, Xue Zhang:
Soft Image Segmentation Using Gradient Graph Laplacian Regularizer. ICASSP 2024: 9526-9530 - [c185]Saghar Bagheri, Gene Cheung, Tim Eadie, Antonio Ortega:
Joint Signal Interpolation / Time-Varying Graph Estimation Via Smoothness and Low-Rank Priors. ICASSP 2024: 9646-9650 - [i50]Yasaman Parhizkar, Gene Cheung, Andrew W. Eckford:
Signal Processing in the Retina: Interpretable Graph Classifier to Predict Ganglion Cell Responses. CoRR abs/2401.01813 (2024) - [i49]Tam Thuc Do, Parham Eftekhar, Seyed Alireza Hosseini, Gene Cheung, Philip A. Chou:
Interpretable Lightweight Transformer via Unrolling of Learned Graph Smoothness Priors. CoRR abs/2406.04090 (2024) - [i48]Sadid Sahami, Gene Cheung, Chia-Wen Lin:
Graph Unfolding and Sampling for Transitory Video Summarization via Gershgorin Disc Alignment. CoRR abs/2408.01859 (2024) - [i47]Seyed Alireza Hosseini, Tam Thuc Do, Gene Cheung, Yuichi Tanaka:
Constructing an Interpretable Deep Denoiser by Unrolling Graph Laplacian Regularizer. CoRR abs/2409.06676 (2024) - [i46]Haruki Yokota, Hiroshi Higashi, Yuichi Tanaka, Gene Cheung:
Efficient Learning of Balanced Signed Graphs via Iterative Linear Programming. CoRR abs/2409.07794 (2024) - 2023
- [j79]Chinthaka Dinesh, Gene Cheung, Ivan V. Bajic:
Point Cloud Sampling via Graph Balancing and Gershgorin Disc Alignment. IEEE Trans. Pattern Anal. Mach. Intell. 45(1): 868-886 (2023) - [j78]Fen Wang, Gene Cheung, Minxiang Ye, Taihao Li, Yi-Tian Feng:
Fast MSE-Based Sampling of Bandlimited Graph Signals via Low-Pass Impulse Responses. IEEE Trans. Signal Process. 71: 4207-4223 (2023) - [c184]Haruki Yokota, Junya Hara, Yuichi Tanaka, Gene Cheung:
Signed Graph Balancing with Graph Cut. EUSIPCO 2023: 1853-1857 - [c183]Chinthaka Dinesh, Gene Cheung, Fei Chen, Yuejiang Li, H. Vicky Zhao:
Modeling Viral Information Spreading via Directed Acyclic Graph Diffusion. GLOBECOM 2023: 1179-1184 - [c182]Tam Thuc Do, Philip A. Chou, Gene Cheung:
Volumetric Attribute Compression for 3D Point Clouds Using Feedforward Network with Geometric Attention. ICASSP 2023: 1-5 - [c181]Fengbo Lan, Gene Cheung, Prabhkirat Arora, Deinabo Richard-Koko, Lisa Cole:
On Designing A 3d Imaging Summer Project For Ontario's High School Students During Covid-19 Pandemic. ICASSP 2023: 1-5 - [c180]Yuejiang Li, H. Vicky Zhao, Gene Cheung:
Eigen-Decomposition-Free Directed Graph Sampling via Gershgorin Disc Alignment. ICASSP 2023: 1-5 - [c179]Jin Zeng, Yang Liu, Gene Cheung, Wei Hu:
Sparse Graph Learning with Spectrum Prior for Deep Graph Convolutional Networks. ICASSP 2023: 1-5 - [c178]Yeganeh Gharedaghi, Gene Cheung, Xianming Liu:
Retinex-based Image Denoising / Contrast Enhancement Using Gradient Graph Laplacian Regularizer. ICIP 2023: 2710-2714 - [c177]Saghar Bagheri, Gene Cheung, Timothy Eadie:
Graph Sparsification for GCN Towards Optimal Crop Yield Predictions. IGARSS 2023: 1712-1715 - [c176]Chinthaka Dinesh, Junfei Wang, Gene Cheung, Pirathayini Srikantha:
Complex Graph Laplacian Regularizer for Inferencing Grid States. SmartGridComm 2023: 1-6 - [i45]Tam Thuc Do, Philip A. Chou, Gene Cheung:
Volumetric Attribute Compression for 3D Point Clouds using Feedforward Network with Geometric Attention. CoRR abs/2304.00335 (2023) - [i44]Chinthaka Dinesh, Gene Cheung, Fei Chen, Yuejiang Li, H. Vicky Zhao:
Modeling Viral Information Spreading via Directed Acyclic Graph Diffusion. CoRR abs/2305.05107 (2023) - [i43]Saghar Bagheri, Gene Cheung, Timothy Eadie:
Graph Sparsification for GCN Towards Optimal Crop Yield Predictions. CoRR abs/2306.01725 (2023) - [i42]Yeganeh Gharedaghi, Gene Cheung, Xianming Liu:
Retinex-based Image Denoising / Contrast Enhancement using Gradient Graph Laplacian Regularizer. CoRR abs/2307.02625 (2023) - [i41]Tam Thuc Do, Philip A. Chou, Gene Cheung:
Learned Nonlinear Predictor for Critically Sampled 3D Point Cloud Attribute Compression. CoRR abs/2311.13539 (2023) - 2022
- [j77]Cheng Yang, Gene Cheung, Wei Hu:
Signed Graph Metric Learning via Gershgorin Disc Perfect Alignment. IEEE Trans. Pattern Anal. Mach. Intell. 44(10): 7219-7234 (2022) - [j76]Yuan Yuan, Gene Cheung, Pascal Frossard, H. Vicky Zhao, Jiwu Huang:
Landmarking for Navigational Streaming of Stored High-Dimensional Media. IEEE Trans. Circuits Syst. Video Technol. 32(8): 5663-5679 (2022) - [j75]Yung-Hsuan Chao, Haoran Hong, Gene Cheung, Antonio Ortega:
Pre-Demosaic Graph-Based Light Field Image Compression. IEEE Trans. Image Process. 31: 1816-1829 (2022) - [j74]Chinthaka Dinesh, Gene Cheung, Ivan V. Bajic:
Point Cloud Video Super-Resolution via Partial Point Coupling and Graph Smoothness. IEEE Trans. Image Process. 31: 4117-4132 (2022) - [j73]Xue Zhang, Gene Cheung, Jiahao Pang, Yash Sanghvi, Abhiram Gnanasambandam, Stanley H. Chan:
Graph-Based Depth Denoising & Dequantization for Point Cloud Enhancement. IEEE Trans. Image Process. 31: 6863-6878 (2022) - [j72]Fen Wang, Gene Cheung, Taihao Li, Ying Du, Yu-Ping Ruan:
Fast Sampling and Reconstruction for Linear Inverse Problems: From Vectors to Tensors. IEEE Trans. Signal Process. 70: 6376-6391 (2022) - [c175]Saghar Bagheri, Chinthaka Dinesh, Gene Cheung, Timothy Eadie:
Unsupervised Graph Spectral Feature Denoising for Crop Yield Prediction. EUSIPCO 2022: 1986-1990 - [c174]Fen Wang, Taihao Li, Ying Du, Yu-Ping Ruan, Gene Cheung:
Fast Sampling for Large-scale Linear Inverse Problems via Enlarging Principle Submatrix. EUSIPCO 2022: 2266-2270 - [c173]Sadid Sahami, Gene Cheung, Chia-Wen Lin:
Fast Graph Sampling for Short Video Summarization Using Gershgorin Disc Alignment. ICASSP 2022: 1765-1769 - [c172]Chinthaka Dinesh, Saghar Bagheri, Gene Cheung, Ivan V. Bajic:
Linear-Time Sampling on Signed Graphs Via Gershgorin Disc Perfect Alignment. ICASSP 2022: 5942-5946 - [c171]Rino Yoshida, Kazuya Kodama, Huy Vu, Gene Cheung, Takayuki Hamamoto:
Unrolling Graph Total Variation for Light Field Image Denoising. ICIP 2022: 1262-2166 - [c170]Saghar Bagheri, Tam Thuc Do, Gene Cheung, Antonio Ortega:
Hybrid Model-Based / Data-Driven Graph Transform for Image Coding. ICIP 2022: 3667-3671 - [i40]Jin Zeng, Saghar Bagheri, Yang Liu, Gene Cheung, Wei Hu:
Sparse Graph Learning with Eigen-gap for Spectral Filter Training in Graph Convolutional Networks. CoRR abs/2202.13526 (2022) - [i39]Saghar Bagheri, Tam Thuc Do, Gene Cheung, Antonio Ortega:
Hybrid Model-based / Data-driven Graph Transform for Image Coding. CoRR abs/2203.01186 (2022) - [i38]Saghar Bagheri, Chinthaka Dinesh, Gene Cheung, Timothy Eadie:
Unsupervised Graph Spectral Feature Denoising for Crop Yield Prediction. CoRR abs/2208.02714 (2022) - [i37]Chinthaka Dinesh, Gene Cheung, Saghar Bagheri, Ivan V. Bajic:
Efficient Signed Graph Sampling via Balancing & Gershgorin Disc Perfect Alignment. CoRR abs/2208.08726 (2022) - 2021
- [j71]Xue Zhang, Gene Cheung, Yao Zhao, Patrick Le Callet, Chunyu Lin, Jack Z. G. Tan:
Graph Learning Based Head Movement Prediction for Interactive 360 Video Streaming. IEEE Trans. Image Process. 30: 4622-4636 (2021) - [j70]Minxiang Ye, Vladimir Stankovic, Lina Stankovic, Gene Cheung:
Robust Deep Graph Based Learning for Binary Classification. IEEE Trans. Signal Inf. Process. over Networks 7: 322-335 (2021) - [c169]Huy Vu, Gene Cheung, Yonina C. Eldar:
Unrolling of Deep Graph Total Variation for Image Denoising. ICASSP 2021: 2050-2054 - [c168]Fen Wang, Gene Cheung, Yongchao Wang, Wai-Tian Tan:
Fast Manifold Landmarking Using Extreme Eigen-Pairs. ICASSP 2021: 3700-3704 - [c167]Saghar Bagheri, Gene Cheung, Antonio Ortega, Fen Wang:
Learning Sparse Graph Laplacian with K Eigenvector Prior via Iterative Glasso and Projection. ICASSP 2021: 5365-5369 - [c166]Fei Chen, Gene Cheung, Xue Zhang:
Fast & Robust Image Interpolation Using Gradient Graph Laplacian Regularizer. ICIP 2021: 1964-1968 - [i36]Yuan Yuan, Gene Cheung, Pascal Frossard, H. Vicky Zhao, Jiwu Huang:
Landmarking for Navigational Streaming of Stored High-Dimensional Media. CoRR abs/2104.06876 (2021) - [i35]Cheng Yang, Gene Cheung, Wai-tian Tan, Guangtao Zhai:
Projection-free Graph-based Classifier Learning using Gershgorin Disc Perfect Alignment. CoRR abs/2106.01642 (2021) - [i34]Cheng Yang, Gene Cheung, Wai-tian Tan, Guangtao Zhai:
Unfolding Projection-free SDP Relaxation of Binary Graph Classifier via GDPA Linearization. CoRR abs/2109.04697 (2021) - [i33]Sadid Sahami, Gene Cheung, Chia-Wen Lin:
Fast Graph Sampling for Short Video Summarization using Gershgorin Disc Alignment. CoRR abs/2110.11420 (2021) - [i32]Xue Zhang, Gene Cheung, Jiahao Pang, Yash Sanghvi, Abhiram Gnanasambandam, Stanley H. Chan:
Graph-Based Depth Denoising & Dequantization for Point Cloud Enhancement. CoRR abs/2111.04946 (2021) - [i31]Fei Chen, Gene Cheung, Xue Zhang:
Fast Computation of Generalized Eigenvectors for Manifold Graph Embedding. CoRR abs/2112.07862 (2021) - 2020
- [j69]Yuichi Tanaka, Yonina C. Eldar, Antonio Ortega, Gene Cheung:
Sampling Signals on Graphs: From Theory to Applications. IEEE Signal Process. Mag. 37(6): 14-30 (2020) - [j68]Jin Zeng, Gene Cheung, Michael Ng, Jiahao Pang, Cheng Yang:
3D Point Cloud Denoising Using Graph Laplacian Regularization of a Low Dimensional Manifold Model. IEEE Trans. Image Process. 29: 3474-3489 (2020) - [j67]Chinthaka Dinesh, Gene Cheung, Ivan V. Bajic:
Point Cloud Denoising via Feature Graph Laplacian Regularization. IEEE Trans. Image Process. 29: 4143-4158 (2020) - [j66]Yuanchao Bai, Fen Wang, Gene Cheung, Yuji Nakatsukasa, Wen Gao:
Fast Graph Sampling Set Selection Using Gershgorin Disc Alignment. IEEE Trans. Signal Process. 68: 2419-2434 (2020) - [j65]Fen Wang, Yongchao Wang, Gene Cheung, Cheng Yang:
Graph Sampling for Matrix Completion Using Recurrent Gershgorin Disc Shift. IEEE Trans. Signal Process. 68: 2814-2829 (2020) - [j64]Wei Hu, Xiang Gao, Gene Cheung, Zongming Guo:
Feature Graph Learning for 3D Point Cloud Denoising. IEEE Trans. Signal Process. 68: 2841-2856 (2020) - [c165]Chinthaka Dinesh, Gene Cheung, Ivan V. Bajic:
Super-Resolution of 3D Color Point Clouds Via Fast Graph Total Variation. ICASSP 2020: 1983-1987 - [c164]Xiaochong Jiang, Cheng Yang, Gene Cheung, Seishi Takamura:
Semi-Regular Geometric Kernel Encoding & Reconstruction for Video Compression. ICASSP 2020: 2183-2187 - [c163]Xue Zhang, Gene Cheung, Patrick Le Callet, Jack Z. G. Tan:
Sparse Directed Graph Learning for Head Movement Prediction in 360 Video Streaming. ICASSP 2020: 2678-2682 - [c162]Cheng Yang, Gene Cheung, Wei Hu:
Graph Metric Learning via Gershgorin Disc Alignment. ICASSP 2020: 5530-5534 - [c161]Weng-Tai Su, Gene Cheung, Richard Wildes, Chia-Wen Lin:
Graph Neural Net Using Analytical Graph Filters and Topology Optimization for Image Denoising. ICASSP 2020: 8464-8468 - [c160]Fengbo Lan, Cheng Yang, Gene Cheung, Jack Z. G. Tan:
Joint Demosaicking / Rectification Of Fisheye Camera Images Using Multi-Color Graph Laplacian Regularization. ICIP 2020: 2596-2600 - [c159]Chinthaka Dinesh, Gene Cheung, Fen Wang, Ivan V. Bajic:
Sampling Of 3d Point Cloud Via Gershgorin Disc Alignment. ICIP 2020: 2736-2740 - [c158]Xue Zhang, Gene Cheung, Jiahao Pang, Dong Tian:
3D Point Cloud Enhancement Using Graph-Modelled Multiview Depth Measurements. ICIP 2020: 3314-3318 - [i30]Cheng Yang, Gene Cheung, Wei Hu:
Fast Graph Metric Learning via Gershgorin Disc Alignment. CoRR abs/2001.10485 (2020) - [i29]Xue Zhang, Gene Cheung, Jiahao Pang, Dong Tian:
3D Point Cloud Enhancement using Graph-Modelled Multiview Depth Measurements. CoRR abs/2002.04537 (2020) - [i28]Yuichi Tanaka, Yonina C. Eldar, Antonio Ortega, Gene Cheung:
Sampling on Graphs: From Theory to Applications. CoRR abs/2003.03957 (2020) - [i27]Cheng Yang, Gene Cheung, Wei Hu:
Signed Graph Metric Learning via Gershgorin Disc Alignment. CoRR abs/2006.08816 (2020) - [i26]Huy Vu, Gene Cheung, Yonina C. Eldar:
Unrolling of Deep Graph Total Variation for Image Denoising. CoRR abs/2010.11290 (2020) - [i25]Saghar Bagheri, Gene Cheung, Antonio Ortega, Fen Wang:
Learning Sparse Graph Laplacian with K Eigenvector Prior via Iterative GLASSO and Projection. CoRR abs/2010.13179 (2020)
2010 – 2019
- 2019
- [j63]Xianming Liu, Gene Cheung, Xiangyang Ji, Debin Zhao, Wen Gao:
Graph-Based Joint Dequantization and Contrast Enhancement of Poorly Lit JPEG Images. IEEE Trans. Image Process. 28(3): 1205-1219 (2019) - [j62]Yuanchao Bai, Gene Cheung, Xianming Liu, Wen Gao:
Graph-Based Blind Image Deblurring From a Single Photograph. IEEE Trans. Image Process. 28(3): 1404-1418 (2019) - [j61]Chih-Chung Hsu, Chia-Wen Lin, Weng-Tai Su, Gene Cheung:
SiGAN: Siamese Generative Adversarial Network for Identity-Preserving Face Hallucination. IEEE Trans. Image Process. 28(12): 6225-6236 (2019) - [j60]Fen Wang, Gene Cheung, Yongchao Wang:
Low-complexity Graph Sampling With Noise and Signal Reconstruction via Neumann Series. IEEE Trans. Signal Process. 67(21): 5511-5526 (2019) - [c157]Jin Zeng, Jiahao Pang, Wenxiu Sun, Gene Cheung:
Deep Graph Laplacian Regularization for Robust Denoising of Real Images. CVPR Workshops 2019: 1759-1768 - [c156]Minxiang Ye, Vladimir Stankovic, Lina Stankovic, Gene Cheung:
Deep Graph Regularized Learning for Binary Classification. ICASSP 2019: 3537-3541 - [c155]Yuanchao Bai, Gene Cheung, Fen Wang, Xianming Liu, Wen Gao:
Reconstruction-cognizant Graph Sampling Using Gershgorin Disc Alignment. ICASSP 2019: 5396-5400 - [c154]Fen Wang, Gene Cheung, Yongchao Wang:
Fast Sampling of Graph Signals with Noise via Neumann Series Conversion. ICASSP 2019: 5456-5460 - [c153]Chinthaka Dinesh, Gene Cheung, Ivan V. Bajic:
3D Point Cloud Super-Resolution via Graph Total Variation on Surface Normals. ICIP 2019: 4390-4394 - [c152]Chinthaka Dinesh, Gene Cheung, Ivan V. Bajic:
3D Point Cloud Color Denoising Using Convex Graph-Signal Smoothness Priors. MMSP 2019: 1-6 - [i24]Wei Hu, Xiang Gao, Gene Cheung, Zongming Guo:
Feature Graph Learning for 3D Point Cloud Denoising. CoRR abs/1907.09138 (2019) - [i23]Minxiang Ye, Vladimir Stankovic, Lina Stankovic, Gene Cheung:
Robust Deep Graph Based Learning for Binary Classification. CoRR abs/1912.03321 (2019) - 2018
- [j59]Jack Z. G. Tan, Gene Cheung, Rui Ma:
360-Degree Virtual-Reality Cameras for the Masses. IEEE Multim. 25(1): 87-94 (2018) - [j58]Gene Cheung, Enrico Magli, Yuichi Tanaka, Michael K. Ng:
Graph Spectral Image Processing. Proc. IEEE 106(5): 907-930 (2018) - [j57]Ana De Abreu, Gene Cheung, Pascal Frossard, Fernando Pereira:
Optimal Lagrange multipliers for dependent rate allocation in video coding. Signal Process. Image Commun. 63: 113-124 (2018) - [j56]Fen Wang, Yongchao Wang, Gene Cheung:
A-Optimal Sampling and Robust Reconstruction for Graph Signals via Truncated Neumann Series. IEEE Signal Process. Lett. 25(5): 680-684 (2018) - [j55]Chinthaka Dinesh, Ivan V. Bajic, Gene Cheung:
Adaptive Nonrigid Inpainting of Three-Dimensional Point Cloud Geometry. IEEE Signal Process. Lett. 25(6): 878-882 (2018) - [j54]Yuan Yuan, Gene Cheung, Patrick Le Callet, Pascal Frossard, H. Vicky Zhao:
Object Shape Approximation and Contour Adaptive Depth Image Coding for Virtual View Synthesis. IEEE Trans. Circuits Syst. Video Technol. 28(12): 3437-3451 (2018) - [j53]Xianming Liu, Gene Cheung, Chia-Wen Lin, Debin Zhao, Wen Gao:
Prior-Based Quantization Bin Matching for Cloud Storage of JPEG Images. IEEE Trans. Image Process. 27(7): 3222-3235 (2018) - [j52]Amin Zheng, Gene Cheung, Dinei Florêncio:
Joint Denoising/Compression of Image Contours via Shape Prior and Context Tree. IEEE Trans. Image Process. 27(7): 3332-3344 (2018) - [j51]Gene Cheung, Weng-Tai Su, Yu Mao, Chia-Wen Lin:
Robust Semisupervised Graph Classifier Learning With Negative Edge Weights. IEEE Trans. Signal Inf. Process. over Networks 4(4): 712-726 (2018) - [c151]Cheng Yang, Gene Cheung, Vladimir Stankovic:
Alternating Binary Classifier and Graph Learning from Partial Labels. APSIPA 2018: 1137-1140 - [c150]Weihang Liao, Gene Cheung, Shogo Muramatsu, Hiroyasu Yasuda, Kiyoshi Hayasaka:
Graph Learning & Fast Transform Coding of 3D River Data. APSIPA 2018: 1313-1317 - [c149]Shuai Yang, Gene Cheung, Jiaying Liu, Zongming Guo:
Soft Decoding of Light Field Images Using Pocs and Fast Graph Spectrayl Filters. ICASSP 2018: 1713-1717 - [c148]Yuanchao Bai, Gene Cheung, Xianming Liu, Wen Gao:
Blind Image Deblurring Via Reweighted Graph Total Variation. ICASSP 2018: 1822-1826 - [c147]Weihang Liao, Gene Cheung, Wei Hu:
Path Coding on Geometric Planar Graph for 2D / 3D Visual Data Partitioning. ICIP 2018: 116-120 - [c146]Qi Chang, Gene Cheung, Yao Zhao, Xiaolong Li, Rongrong Ni:
Non-Local Graph-Based Prediction for Reversible Data Hiding in Images. ICIP 2018: 1693-1697 - [c145]Weng-Tai Su, Chih-Chung Hsu, Ziling Huang, Chia-Wen Lin, Gene Cheung:
Joint Pairwise Learning and Image Clustering Based on a Siamese CNN. ICIP 2018: 1992-1996 - [c144]Eduardo Peixoto, Bruno Macchiavello, Edson Mintsu Hung, Gene Cheung:
Progressive Sub-Aperture Image Recovery for Interactive Light Field Data Streaming. ICIP 2018: 3289-3293 - [c143]Cheng Yang, Gene Cheung, Seishi Takamura:
RD-Optimized 3D Planar Model Reconstruction & Encoding for Video Compression. ICIP 2018: 3613-3617 - [c142]Suiyi Ling, Gene Cheung, Patrick Le Callet:
No-Reference Quality Assessment for Stitched Panoramic Images Using Convolutional Sparse Coding and Compound Feature Selection. ICME 2018: 1-6 - [c141]Chinthaka Dinesh, Gene Cheung, Ivan V. Bajic, Cheng Yang:
Local 3D Point Cloud Denoising via Bipartite Graph Approximation & Total Variation. MMSP 2018: 1-6 - [c140]Wallace Bruno S. de Souza, Bruno Macchiavello, Eduardo Peixoto, Edson M. Hung, Gene Cheung:
A Sub-Aperture Image Selection Refinement Method for Progressive Light Field Transmission. MMSP 2018: 1-6 - [i22]Qi Chang, Gene Cheung, Yao Zhao, Xiaolong Li, Rongrong Ni:
Non-Local Graph-Based Prediction For Reversible Data Hiding In Images. CoRR abs/1802.06935 (2018) - [i21]Yuanchao Bai, Gene Cheung, Xianming Liu, Wen Gao:
Graph-Based Blind Image Deblurring From a Single Photograph. CoRR abs/1802.07929 (2018) - [i20]Jin Zeng, Gene Cheung, Michael Ng, Jiahao Pang, Cheng Yang:
3D Point Cloud Denoising using Graph Laplacian Regularization of a Low Dimensional Manifold Model. CoRR abs/1803.07252 (2018) - [i19]Chih-Chung Hsu, Chia-Wen Lin, Weng-Tai Su, Gene Cheung:
SiGAN: Siamese Generative Adversarial Network for Identity-Preserving Face Hallucination. CoRR abs/1807.08370 (2018) - [i18]Jin Zeng, Jiahao Pang, Wenxiu Sun, Gene Cheung, Ruichao Xiao:
Deep Graph Laplacian Regularization. CoRR abs/1807.11637 (2018) - 2017
- [j50]Xianming Liu, Gene Cheung, Xiaolin Wu, Debin Zhao:
Random Walk Graph Laplacian-Based Smoothness Prior for Soft Decoding of JPEG Images. IEEE Trans. Image Process. 26(2): 509-524 (2017) - [j49]