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09/12/2023
Frequency Convergence of Complexon Shift Operators (Extended Version)
Topological Signal Processing (TSP) utilizes simplicial complexes to mod...
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07/15/2023
ExposureDiffusion: Learning to Expose for Low-light Image Enhancement
Previous raw image-based low-light image enhancement methods predominant...
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07/09/2023
Enhancing Low-Light Images Using Infrared-Encoded Images
Low-light image enhancement task is essential yet challenging as it is i...
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06/23/2023
WBCAtt: A White Blood Cell Dataset Annotated with Detailed Morphological Attributes
The examination of blood samples at a microscopic level plays a fundamen...
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06/21/2023
Beyond Learned Metadata-based Raw Image Reconstruction
While raw images have distinct advantages over sRGB images, e.g., linear...
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05/15/2023
Denoising Diffusion Models for Plug-and-Play Image Restoration
Plug-and-play Image Restoration (IR) has been widely recognized as a fle...
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03/03/2023
Unsupervised Deep Digital Staining For Microscopic Cell Images Via Knowledge Distillation
Staining is critical to cell imaging and medical diagnosis, which is exp...
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03/03/2023
Benchmarking White Blood Cell Classification Under Domain Shift
Recognizing the types of white blood cells (WBCs) in microscopic images ...
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02/25/2023
Raw Image Reconstruction with Learned Compact Metadata
While raw images exhibit advantages over sRGB images (e.g., linearity an...
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02/11/2023
Removing Image Artifacts From Scratched Lens Protectors
A protector is placed in front of the camera lens for mobile devices to ...
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02/03/2023
ShadowFormer: Global Context Helps Image Shadow Removal
Recent deep learning methods have achieved promising results in image sh...
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12/20/2022
Temporal Output Discrepancy for Loss Estimation-based Active Learning
While deep learning succeeds in a wide range of tasks, it highly depends...
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10/05/2022
Making Your First Choice: To Address Cold Start Problem in Vision Active Learning
Active learning promises to improve annotation efficiency by iteratively...
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09/13/2022
Learning to Solve Multiple-TSP with Time Window and Rejections via Deep Reinforcement Learning
We propose a manager-worker framework based on deep reinforcement learni...
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07/25/2022
REPNP: Plug-and-Play with Deep Reinforcement Learning Prior for Robust Image Restoration
Image restoration schemes based on the pre-trained deep models have rece...
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06/10/2022
ABCDE: An Agent-Based Cognitive Development Environment
Children's cognitive abilities are sometimes cited as AI benchmarks. How...
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01/10/2022
Enhancing Low-Light Images in Real World via Cross-Image Disentanglement
Images captured in the low-light condition suffer from low visibility an...
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11/11/2021
FINO: Flow-based Joint Image and Noise Model
One of the fundamental challenges in image restoration is denoising, whe...
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10/15/2021
Adversarial Purification through Representation Disentanglement
Deep learning models are vulnerable to adversarial examples and make inc...
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09/26/2021
Disentangled Feature Representation for Few-shot Image Classification
Learning the generalizable feature representation is critical for few-sh...
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09/10/2021
PIP: Physical Interaction Prediction via Mental Imagery with Span Selection
To align advanced artificial intelligence (AI) with human values and pro...
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07/13/2021
ReLLIE: Deep Reinforcement Learning for Customized Low-Light Image Enhancement
Low-light image enhancement (LLIE) is a pervasive yet challenging proble...
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07/12/2021
R3L: Connecting Deep Reinforcement Learning to Recurrent Neural Networks for Image Denoising via Residual Recovery
State-of-the-art image denoisers exploit various types of deep neural ne...
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06/01/2021
Reconciliation of Statistical and Spatial Sparsity For Robust Image and Image-Set Classification
Recent image classification algorithms, by learning deep features from l...
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03/01/2021
Systematic Analysis and Removal of Circular Artifacts for StyleGAN
StyleGAN is one of the state-of-the-art image generators which is well-k...
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02/02/2021
Recent Advances in Adversarial Training for Adversarial Robustness
Adversarial training is one of the most effective approaches defending a...
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01/14/2021
Joint Dimensionality Reduction for Separable Embedding Estimation
Low-dimensional embeddings for data from disparate sources play critical...
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09/21/2020
Feature Distillation With Guided Adversarial Contrastive Learning
Deep learning models are shown to be vulnerable to adversarial examples....
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08/02/2020
Removing Backdoor-Based Watermarks in Neural Networks with Limited Data
Deep neural networks have been widely applied and achieved great success...
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07/14/2020
Attentive Graph Neural Networks for Few-Shot Learning
Graph Neural Networks (GNN) has demonstrated the superior performance in...
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06/24/2020
Self-Convolution: A Highly-Efficient Operator for Non-Local Image Restoration
Constructing effective image priors is critical to solving ill-posed inv...
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06/14/2020
Hyper RPCA: Joint Maximum Correntropy Criterion and Laplacian Scale Mixture Modeling On-the-Fly for Moving Object Detection
Moving object detection is critical for automated video analysis in many...
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05/16/2020
The Power of Triply Complementary Priors for Image Compressive Sensing
Recent works that utilized deep models have achieved superior results in...
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03/29/2020
A Set-Theoretic Study of the Relationships of Image Models and Priors for Restoration Problems
Image prior modeling is the key issue in image recovery, computational i...
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05/22/2019
Segmentation-Aware Image Denoising without Knowing True Segmentation
Several recent works discussed application-driven image restoration neur...
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03/25/2019
Transform Learning for Magnetic Resonance Image Reconstruction: From Model-based Learning to Building Neural Networks
Magnetic resonance imaging (MRI) is widely used in clinical practice for...
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09/06/2018
Connecting Image Denoising and High-Level Vision Tasks via Deep Learning
Image denoising and high-level vision tasks are usually handled independ...
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08/03/2018
The Power of Complementary Regularizers: Image Recovery via Transform Learning and Low-Rank Modeling
Recent works on adaptive sparse and on low-rank signal modeling have dem...
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06/07/2018
Non-Local Recurrent Network for Image Restoration
Many classic methods have shown non-local self-similarity in natural ima...
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10/03/2017
VIDOSAT: High-dimensional Sparsifying Transform Learning for Online Video Denoising
Techniques exploiting the sparsity of images in a transform domain have ...
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06/14/2017
When Image Denoising Meets High-Level Vision Tasks: A Deep Learning Approach
Conventionally, image denoising and high-level vision tasks are handled ...
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06/09/2016
Machine Learning Techniques and Applications For Ground-based Image Analysis
Ground-based whole sky cameras have opened up new opportunities for moni...
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01/27/2016
