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07/05/2023
Retinex-based Image Denoising / Contrast Enhancement using Gradient Graph Laplacian Regularizer
Images captured in poorly lit conditions are often corrupted by acquisit...
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05/28/2023
Backdoor Attacks Against Incremental Learners: An Empirical Evaluation Study
Large amounts of incremental learning algorithms have been proposed to a...
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04/06/2023
Super-Resolving Face Image by Facial Parsing Information
Face super-resolution is a technology that transforms a low-resolution f...
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03/24/2023
Image Deblurring by Exploring In-depth Properties of Transformer
Image deblurring continues to achieve impressive performance with the de...
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02/19/2023
Guided Depth Map Super-resolution: A Survey
Guided depth map super-resolution (GDSR), which aims to reconstruct a hi...
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10/05/2022
Multi-Camera Collaborative Depth Prediction via Consistent Structure Estimation
Depth map estimation from images is an important task in robotic systems...
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09/11/2022
Deep Lossy Plus Residual Coding for Lossless and Near-lossless Image Compression
Lossless and near-lossless image compression is of paramount importance ...
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09/02/2022
LiteDepth: Digging into Fast and Accurate Depth Estimation on Mobile Devices
Monocular depth estimation is an essential task in the computer vision c...
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06/23/2022
Prototype-Anchored Learning for Learning with Imperfect Annotations
The success of deep neural networks greatly relies on the availability o...
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06/23/2022
Learning Towards the Largest Margins
One of the main challenges for feature representation in deep learning-b...
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05/25/2022
ReSmooth: Detecting and Utilizing OOD Samples when Training with Data Augmentation
Data augmentation (DA) is a widely used technique for enhancing the trai...
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05/23/2022
Towards Model Generalization for Monocular 3D Object Detection
Monocular 3D object detection (Mono3D) has achieved tremendous improveme...
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04/25/2022
Unsupervised Domain Adaptation for Monocular 3D Object Detection via Self-Training
Monocular 3D object detection (Mono3D) has achieved unprecedented succes...
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04/18/2022
Self-Supervised Arbitrary-Scale Point Clouds Upsampling via Implicit Neural Representation
Point clouds upsampling is a challenging issue to generate dense and uni...
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04/03/2022
BinsFormer: Revisiting Adaptive Bins for Monocular Depth Estimation
Monocular depth estimation is a fundamental task in computer vision and ...
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03/27/2022
DepthFormer: Exploiting Long-Range Correlation and Local Information for Accurate Monocular Depth Estimation
This paper aims to address the problem of supervised monocular depth est...
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03/10/2022
Exploiting the Potential of Datasets: A Data-Centric Approach for Model Robustness
Robustness of deep neural networks (DNNs) to malicious perturbations is ...
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03/08/2022
Shadows can be Dangerous: Stealthy and Effective Physical-world Adversarial Attack by Natural Phenomenon
Estimating the risk level of adversarial examples is essential for safel...
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12/17/2021
Towards End-to-End Image Compression and Analysis with Transformers
We propose an end-to-end image compression and analysis model with Trans...
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12/13/2021
Deep Attentional Guided Image Filtering
Guided filter is a fundamental tool in computer vision and computer grap...
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12/09/2021
SimIPU: Simple 2D Image and 3D Point Cloud Unsupervised Pre-Training for Spatial-Aware Visual Representations
Pre-training has become a standard paradigm in many computer vision task...
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11/27/2021
Learning A 3D-CNN and Transformer Prior for Hyperspectral Image Super-Resolution
To solve the ill-posed problem of hyperspectral image super-resolution (...
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09/23/2021
Weakly-Supervised Monocular Depth Estimationwith Resolution-Mismatched Data
Depth estimation from a single image is an active research topic in comp...
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08/31/2021
Spectral Splitting and Aggregation Network for Hyperspectral Face Super-Resolution
High-resolution (HR) hyperspectral face image plays an important role in...
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07/31/2021
Learning with Noisy Labels via Sparse Regularization
Learning with noisy labels is an important and challenging task for trai...
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06/06/2021
Asymmetric Loss Functions for Learning with Noisy Labels
Robust loss functions are essential for training deep neural networks wi...
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05/31/2021
BaMBNet: A Blur-aware Multi-branch Network for Defocus Deblurring
The defocus deblurring raised from the finite aperture size and exposure...
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04/04/2021
High-resolution Depth Maps Imaging via Attention-based Hierarchical Multi-modal Fusion
Depth map records distance between the viewpoint and objects in the scen...
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03/31/2021
Learning Scalable ℓ_∞-constrained Near-lossless Image Compression via Joint Lossy Image and Residual Compression
We propose a novel joint lossy image and residual compression framework ...
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01/11/2021
Deep Learning-based Face Super-resolution: A Survey
Face super-resolution, also known as face hallucination, which is aimed ...
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10/15/2020
Unsupervised Constrative Person Re-identification
Person re-identification (ReID) aims at searching the same identity pers...
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06/09/2020
Single Image Deraining via Scale-space Invariant Attention Neural Network
Image enhancement from degradation of rainy artifacts plays a critical r...
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05/18/2020
Learning Spatial-Spectral Prior for Super-Resolution of Hyperspectral Imagery
Recently, single gray/RGB image super-resolution reconstruction task has...
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03/17/2020
Rectified Meta-Learning from Noisy Labels for Robust Image-based Plant Disease Diagnosis
Plant diseases serve as one of main threats to food security and crop pr...
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03/14/2020
Rapid Whole Slide Imaging via Learning-based Two-shot Virtual Autofocusing
Whole slide imaging (WSI) is an emerging technology for digital patholog...
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03/04/2020
ADRN: Attention-based Deep Residual Network for Hyperspectral Image Denoising
Hyperspectral image (HSI) denoising is of crucial importance for many su...
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12/23/2019
FasterSeg: Searching for Faster Real-time Semantic Segmentation
We present FasterSeg, an automatically designed semantic segmentation ne...
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08/02/2019
Real Time Visual Tracking using Spatial-Aware Temporal Aggregation Network
More powerful feature representations derived from deep neural networks ...
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07/05/2019
Depth Restoration: A fast low-rank matrix completion via dual-graph regularization
As a real scenes sensing approach, depth information obtains the widespr...
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06/11/2019
Single Image Blind Deblurring Using Multi-Scale Latent Structure Prior
Blind image deblurring is a challenging problem in computer vision, whic...
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03/10/2019
NormalNet: Learning based Guided Normal Filtering for Mesh Denoising
Mesh denoising is a critical technology in geometry processing, which ai...
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09/12/2018
Hyperspectral Image Classification in the Presence of Noisy Labels
Label information plays an important role in supervised hyperspectral im...
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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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09/05/2018
An Elementary Proof of a Classical Information-Theoretic Formula
A renowned information-theoretic formula by Shannon expresses the mutual...
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02/22/2018
Graph-Based Blind Image Deblurring From a Single Photograph
Blind image deblurring, i.e., deblurring without knowledge of the blur k...
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12/24/2017
Blind Image Deblurring via Reweighted Graph Total Variation
Blind image deblurring, i.e., deblurring without knowledge of the blur k...
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12/15/2017
Mapping the world population one building at a time
High resolution datasets of population density which accurately map spar...
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07/27/2017
Building Detection from Satellite Images on a Global Scale
In the last several years, remote sensing technology has opened up the p...
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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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12/08/2016
