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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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09/02/2022
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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05/11/2022
Spatial-Temporal Space Hand-in-Hand: Spatial-Temporal Video Super-Resolution via Cycle-Projected Mutual Learning
Spatial-Temporal Video Super-Resolution (ST-VSR) aims to generate super-...
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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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09/16/2021
TANet: A new Paradigm for Global Face Super-resolution via Transformer-CNN Aggregation Network
Recently, face super-resolution (FSR) methods either feed whole face ima...
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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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03/29/2021
Omniscient Video Super-Resolution
Most recent video super-resolution (SR) methods either adopt an iterativ...
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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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03/04/2020
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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05/12/2019
Ensemble Super-Resolution with A Reference Dataset
By developing sophisticated image priors or designing deep(er) architect...
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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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09/03/2018
Context-Patch Face Hallucination Based on Thresholding Locality-constrained Representation and Reproducing Learning
Face hallucination is a technique that reconstruct high-resolution (HR) ...
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06/28/2018
Deep CNN Denoiser and Multi-layer Neighbor Component Embedding for Face Hallucination
Most of the current face hallucination methods, whether they are shallow...
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06/26/2018