b'Xianming Liu'

research

∙ 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...

0 Yeganeh Gharedaghi, et al. ∙

research

∙ 05/28/2023

Backdoor Attacks Against Incremental Learners: An Empirical Evaluation Study

Large amounts of incremental learning algorithms have been proposed to a...

0 Yiqi Zhong, et al. ∙

research

∙ 04/06/2023

Super-Resolving Face Image by Facial Parsing Information

Face super-resolution is a technology that transforms a low-resolution f...

0 Chenyang Wang, et al. ∙

research

∙ 03/24/2023

Image Deblurring by Exploring In-depth Properties of Transformer

Image deblurring continues to achieve impressive performance with the de...

0 Pengwei Liang, et al. ∙

research

∙ 02/19/2023

Guided Depth Map Super-resolution: A Survey

Guided depth map super-resolution (GDSR), which aims to reconstruct a hi...

0 Zhiwei Zhong, et al. ∙

research

∙ 10/05/2022

Multi-Camera Collaborative Depth Prediction via Consistent Structure Estimation

Depth map estimation from images is an important task in robotic systems...

0 Jialei Xu, et al. ∙

research

∙ 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 ...

0 Yuanchao Bai, et al. ∙

research

∙ 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...

0 Zhenyu Li, et al. ∙

research

∙ 06/23/2022

Prototype-Anchored Learning for Learning with Imperfect Annotations

The success of deep neural networks greatly relies on the availability o...

0 Xiong Zhou, et al. ∙

research

∙ 06/23/2022

Learning Towards the Largest Margins

One of the main challenges for feature representation in deep learning-b...

0 Xiong Zhou, et al. ∙

research

∙ 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...

0 Chenyang Wang, et al. ∙

research

∙ 05/23/2022

Towards Model Generalization for Monocular 3D Object Detection

Monocular 3D object detection (Mono3D) has achieved tremendous improveme...

0 Zhenyu Li, et al. ∙

research

∙ 04/25/2022

Unsupervised Domain Adaptation for Monocular 3D Object Detection via Self-Training

Monocular 3D object detection (Mono3D) has achieved unprecedented succes...

0 Zhenyu Li, et al. ∙

research

∙ 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...

0 Wenbo Zhao, et al. ∙

research

∙ 04/03/2022

BinsFormer: Revisiting Adaptive Bins for Monocular Depth Estimation

Monocular depth estimation is a fundamental task in computer vision and ...

1 Zhenyu Li, et al. ∙

research

∙ 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...

0 Zhenyu Li, et al. ∙

research

∙ 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 ...

0 Yiqi Zhong, et al. ∙

research

∙ 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...

1 Yiqi Zhong, et al. ∙

research

∙ 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...

17 Yuanchao Bai, et al. ∙

research

∙ 12/13/2021

Deep Attentional Guided Image Filtering

Guided filter is a fundamental tool in computer vision and computer grap...

0 Zhiwei Zhong, et al. ∙

research

∙ 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...

2 Zhenyu Li, et al. ∙

research

∙ 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 (...

0 Qing Ma, et al. ∙

research

∙ 09/23/2021

Weakly-Supervised Monocular Depth Estimationwith Resolution-Mismatched Data

Depth estimation from a single image is an active research topic in comp...

3 Jialei Xu, et al. ∙

research

∙ 08/31/2021

Spectral Splitting and Aggregation Network for Hyperspectral Face Super-Resolution

High-resolution (HR) hyperspectral face image plays an important role in...

2 Junjun Jiang, et al. ∙

research

∙ 07/31/2021

Learning with Noisy Labels via Sparse Regularization

Learning with noisy labels is an important and challenging task for trai...

0 Xiong Zhou, et al. ∙

research

∙ 06/06/2021

Asymmetric Loss Functions for Learning with Noisy Labels

Robust loss functions are essential for training deep neural networks wi...

0 Xiong Zhou, et al. ∙

research

∙ 05/31/2021

BaMBNet: A Blur-aware Multi-branch Network for Defocus Deblurring

The defocus deblurring raised from the finite aperture size and exposure...

3 Pengwei Liang, et al. ∙

research

∙ 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...

0 Zhiwei Zhong, et al. ∙

research

∙ 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 ...

0 Yuanchao Bai, et al. ∙

research

∙ 01/11/2021

Deep Learning-based Face Super-resolution: A Survey

Face super-resolution, also known as face hallucination, which is aimed ...

72 Junjun Jiang, et al. ∙

research

∙ 10/15/2020

Unsupervised Constrative Person Re-identification

Person re-identification (ReID) aims at searching the same identity pers...

3 Bo Pang, et al. ∙

research

∙ 06/09/2020

Single Image Deraining via Scale-space Invariant Attention Neural Network

Image enhancement from degradation of rainy artifacts plays a critical r...

0 Bo Pang, et al. ∙

research

∙ 05/18/2020

Learning Spatial-Spectral Prior for Super-Resolution of Hyperspectral Imagery

Recently, single gray/RGB image super-resolution reconstruction task has...

4 Junjun Jiang, et al. ∙

research

∙ 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...

10 Ruifeng Shi, et al. ∙

research

∙ 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...

3 Qiang Li, et al. ∙

research

∙ 03/04/2020

ADRN: Attention-based Deep Residual Network for Hyperspectral Image Denoising

Hyperspectral image (HSI) denoising is of crucial importance for many su...

0 Yongsen Zhao, et al. ∙

research

∙ 12/23/2019

FasterSeg: Searching for Faster Real-time Semantic Segmentation

We present FasterSeg, an automatically designed semantic segmentation ne...

0 Wuyang Chen, et al. ∙

research

∙ 08/02/2019

Real Time Visual Tracking using Spatial-Aware Temporal Aggregation Network

More powerful feature representations derived from deep neural networks ...

6 Tao Hu, et al. ∙

research

∙ 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...

3 Wenxiang Zuo, et al. ∙

research

∙ 06/11/2019

Single Image Blind Deblurring Using Multi-Scale Latent Structure Prior

Blind image deblurring is a challenging problem in computer vision, whic...

5 Yuanchao Bai, et al. ∙

research

∙ 03/10/2019

NormalNet: Learning based Guided Normal Filtering for Mesh Denoising

Mesh denoising is a critical technology in geometry processing, which ai...

0 Wenbo Zhao, et al. ∙

research

∙ 09/12/2018

Hyperspectral Image Classification in the Presence of Noisy Labels

Label information plays an important role in supervised hyperspectral im...

8 Junjun Jiang, et al. ∙

research

∙ 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...

0 Ding Liu, et al. ∙

research

∙ 09/05/2018

An Elementary Proof of a Classical Information-Theoretic Formula

A renowned information-theoretic formula by Shannon expresses the mutual...

0 Xianming Liu, et al. ∙

research

∙ 02/22/2018

Graph-Based Blind Image Deblurring From a Single Photograph

Blind image deblurring, i.e., deblurring without knowledge of the blur k...

0 Yuanchao Bai, et al. ∙

research

∙ 12/24/2017

Blind Image Deblurring via Reweighted Graph Total Variation

Blind image deblurring, i.e., deblurring without knowledge of the blur k...

0 Yuanchao Bai, et al. ∙

research

∙ 12/15/2017

Mapping the world population one building at a time

High resolution datasets of population density which accurately map spar...

0 Tobias G. Tiecke, et al. ∙

research

∙ 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...

0 Amy Zhang, et al. ∙

research

∙ 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 ...

0 Ding Liu, et al. ∙

research

∙ 12/08/2016

Feedback Neural Network for Weakly Supervised Geo-Semantic Segmentation

Learning from weakly-supervised data is one of the main challenges in ma...

0 Xianming Liu, et al. ∙

Xianming Liu

Featured Co-authors