| Graph Signal Restoration Using Nested Deep Algorithm Unrolling | 0 | 0.34 | 2022 |
| Graph-Based Depth Denoising & Dequantization for Point Cloud Enhancement. | 0 | 0.34 | 2022 |
| Photon Limited Non-Blind Deblurring Using Algorithm Unrolling | 0 | 0.34 | 2022 |
| Exposure-Referred Signal-to-Noise Ratio for Digital Image Sensors | 0 | 0.34 | 2022 |
| Single Frame Atmospheric Turbulence Mitigation: A Benchmark Study and a New Physics-Inspired Transformer Model. | 0 | 0.34 | 2022 |
| What Does a One-Bit Quanta Image Sensor Offer? | 0 | 0.34 | 2022 |
| Photon-Limited Deblurring Using Algorithm Unrolling. | 0 | 0.34 | 2022 |
| Optical Adversarial Attack | 0 | 0.34 | 2021 |
| Detecting and Segmenting Adversarial Graphics Patterns from Images | 0 | 0.34 | 2021 |
| GRAPH SIGNAL DENOISING USING NESTED-STRUCTURED DEEP ALGORITHM UNROLLING | 0 | 0.34 | 2021 |
| Photon-Limited Object Detection using Non-local Feature Matching and Knowledge Distillation | 0 | 0.34 | 2021 |
| Student-Teacher Learning from Clean Inputs to Noisy Inputs | 0 | 0.34 | 2021 |
| Who Make Drivers Stop? Towards Driver-centric Risk Assessment: Risk Object Identification via Causal Inference | 0 | 0.34 | 2020 |
| Plug-and-Play Methods for Magnetic Resonance Imaging: Using Denoisers for Image Recovery | 3 | 0.38 | 2020 |
| One Size Fits All: Can We Train One Denoiser for All Noise Levels? | 0 | 0.34 | 2020 |
| Simulating Anisoplanatic Turbulence by Sampling Correlated Zernike Coefficients | 0 | 0.34 | 2020 |
| Automatic foreground extraction from imperfect backgrounds using multi-agent consensus equilibrium | 0 | 0.34 | 2020 |
| Learning 3D-aware Egocentric Spatial-Temporal Interaction via Graph Convolutional Networks | 2 | 0.37 | 2020 |
| Rethinking Atmospheric Turbulence Mitigation. | 0 | 0.34 | 2019 |
| Megapixel photon-counting color imaging using quanta image sensor | 3 | 0.39 | 2019 |
| Plug and play methods for magnetic resonance imaging. | 0 | 0.34 | 2019 |
| Optimal Combination of Image Denoisers. | 1 | 0.36 | 2019 |
| Interpolation And Denoising Of Graph Signals Using Plug-And-Play Admm | 0 | 0.34 | 2019 |
| Color Filter Arrays for Quanta Image Sensors. | 1 | 0.37 | 2019 |
| A Super-Resolution and Fusion Approach to Enhancing Hyperspectral Images. | 9 | 0.46 | 2018 |
| Plug-and-Play Unplugged: Optimization-Free Reconstruction Using Consensus Equilibrium | 9 | 0.46 | 2018 |
| Automatic Foreground Extraction using Multi-Agent Consensus Equilibrium. | 0 | 0.34 | 2018 |
| Optimal Threshold Design for Quanta Image Sensor. | 4 | 0.52 | 2018 |
| Performance Analysis of Plug-and-Play ADMM: A Graph Signal Processing Perspective. | 1 | 0.35 | 2018 |
| Integrating Disparate Sources of Experts for Robust Image Denoising. | 1 | 0.36 | 2017 |
| Understanding Symmetric Smoothing Filters: A Gaussian Mixture Model Perspective. | 1 | 0.35 | 2017 |
| Plug-and-Play ADMM for Image Restoration: Fixed-Point Convergence and Applications. | 49 | 1.25 | 2017 |
| Algorithm-Induced Prior for Image Restoration. | 5 | 0.43 | 2016 |
| Images from Bits: Non-Iterative Image Reconstruction for Quanta Image Sensors. | 2 | 0.38 | 2016 |
| Adaptive Image Denoising by Mixture Adaptation. | 17 | 0.54 | 2016 |
| Demystifying Symmetric Smoothing Filters | 3 | 0.39 | 2016 |
| Plug-and-Play ADMM for Image Restoration: Fixed Point Convergence and Applications. | 0 | 0.34 | 2016 |
| Adaptive Patch-Based Image Denoising By Em-Adaptation | 2 | 0.36 | 2015 |
| Depth reconstruction from sparse samples: representation, algorithm, and sampling. | 14 | 0.81 | 2015 |
| Efficient image reconstruction for gigapixel quantum image sensors | 2 | 0.40 | 2014 |
| Adaptive image denoising by targeted databases. | 30 | 0.83 | 2014 |
| Sparse Reconstruction of Depth Data: Representation, Algorithm, and Sampling. | 0 | 0.34 | 2014 |
| Image denoising by targeted external databases | 8 | 0.46 | 2014 |
| A Consistent Histogram Estimator for Exchangeable Graph Models. | 10 | 0.70 | 2014 |
| Stochastic blockmodel approximation of a graphon: Theory and consistent estimation. | 29 | 1.39 | 2013 |
| Estimation of exchangeable graph models by stochastic blockmodel approximation | 1 | 0.37 | 2013 |
| Adaptive Non-Local Means For Multiview Image Denoising: Searching For The Right Patches Via A Statistical Approach | 8 | 0.51 | 2013 |
| Fast Non-Local Filtering By Random Sampling: It Works, Especially For Large Images | 1 | 0.35 | 2013 |
| Monte Carlo Non-Local Means: Random Sampling for Large-Scale Image Filtering. | 21 | 0.79 | 2013 |
| Directional decomposition based total variation image restoration. | 0 | 0.34 | 2012 |
