b'Qinghua Hu'

research

∙ 08/12/2023

Semantic Equivariant Mixup

Mixup is a well-established data augmentation technique, which can exten...

0 Zongbo Han, et al. ∙

research

∙ 07/21/2023

Tuning Pre-trained Model via Moment Probing

Recently, efficient fine-tuning of large-scale pre-trained models has at...

0 Mingze Gao, et al. ∙

research

∙ 06/03/2023

Provable Dynamic Fusion for Low-Quality Multimodal Data

The inherent challenge of multimodal fusion is to precisely capture the ...

0 Qingyang Zhang, et al. ∙

research

∙ 06/02/2023

Calibrating Multimodal Learning

Multimodal machine learning has achieved remarkable progress in a wide r...

0 Huan Ma. Qingyang Zhang, et al. ∙

research

∙ 04/11/2023

Exploring and Exploiting Uncertainty for Incomplete Multi-View Classification

Classifying incomplete multi-view data is inevitable since arbitrary vie...

0 Mengyao Xie, et al. ∙

research

∙ 04/09/2023

Reweighted Mixup for Subpopulation Shift

Subpopulation shift exists widely in many real-world applications, which...

0 Zongbo Han, et al. ∙

research

∙ 03/23/2023

Fairness-guided Few-shot Prompting for Large Language Models

Large language models have demonstrated surprising ability to perform in...

3 Huan Ma, et al. ∙

research

∙ 02/02/2023

MoE-Fusion: Instance Embedded Mixture-of-Experts for Infrared and Visible Image Fusion

Infrared and visible image fusion can compensate for the incompleteness ...

0 Yiming Sun, et al. ∙

research

∙ 12/13/2022

HS-Diffusion: Learning a Semantic-Guided Diffusion Model for Head Swapping

Image-based head swapping task aims to stitch a source head to another s...

0 Qinghe Wang, et al. ∙

research

∙ 08/29/2022

Latent Heterogeneous Graph Network for Incomplete Multi-View Learning

Multi-view learning has progressed rapidly in recent years. Although man...

6 Pengfei Zhu, et al. ∙

research

∙ 07/05/2022

Class-Specific Semantic Reconstruction for Open Set Recognition

Open set recognition enables deep neural networks (DNNs) to identify sam...

0 Hongzhi Huang, et al. ∙

research

∙ 06/30/2022

Multi-Granularity Regularized Re-Balancing for Class Incremental Learning

Deep learning models suffer from catastrophic forgetting when learning n...

0 Huitong Chen, et al. ∙

research

∙ 03/19/2022

Learning Self-Supervised Low-Rank Network for Single-Stage Weakly and Semi-Supervised Semantic Segmentation

Semantic segmentation with limited annotations, such as weakly supervise...

0 Junwen Pan, et al. ∙

research

∙ 01/15/2022

Uncertainty-Aware Multi-View Representation Learning

Learning from different data views by exploring the underlying complemen...

0 Yu Geng, et al. ∙

research

∙ 12/01/2021

Interactive Model with Structural Loss for Language-based Abductive Reasoning

The abductive natural language inference task (αNLI) is proposed to infe...

0 Linhao Li, et al. ∙

research

∙ 11/11/2021

Trustworthy Multimodal Regression with Mixture of Normal-inverse Gamma Distributions

Multimodal regression is a fundamental task, which integrates the inform...

9 Huan Ma, et al. ∙

research

∙ 10/27/2021

Temporal-attentive Covariance Pooling Networks for Video Recognition

For video recognition task, a global representation summarizing the whol...

0 Zilin Gao, et al. ∙

research

∙ 07/30/2021

T-SVDNet: Exploring High-Order Prototypical Correlations for Multi-Source Domain Adaptation

Most existing domain adaptation methods focus on adaptation from only on...

0 Ruihuang Li, et al. ∙

research

∙ 07/19/2021

VisDrone-CC2020: The Vision Meets Drone Crowd Counting Challenge Results

Crowd counting on the drone platform is an interesting topic in computer...

2 Dawei Du, et al. ∙

research

∙ 05/06/2021

Detection, Tracking, and Counting Meets Drones in Crowds: A Benchmark

To promote the developments of object detection, tracking and counting a...

18 Longyin Wen, et al. ∙

research

∙ 11/12/2020

Deep Partial Multi-View Learning

Although multi-view learning has made signifificant progress over the pa...

18 Changqing Zhang, et al. ∙

research

∙ 08/16/2020

SPL-MLL: Selecting Predictable Landmarks for Multi-Label Learning

Although significant progress achieved, multi-label classification is st...

14 Junbing Li, et al. ∙

research

∙ 07/13/2020

Expert Training: Task Hardness Aware Meta-Learning for Few-Shot Classification

Deep neural networks are highly effective when a large number of labeled...

5 Yucan Zhou, et al. ∙

research

∙ 05/07/2020

Enhancing Geometric Factors in Model Learning and Inference for Object Detection and Instance Segmentation

Deep learning-based object detection and instance segmentation have achi...

10 Zhaohui Zheng, et al. ∙

research

∙ 04/26/2020

An Efficient Index Method for the Optimal Route Query over Multi-Cost Networks

Smart city has been consider the wave of the future and the route recomm...

0 Yajun Yang, et al. ∙

research

∙ 03/25/2020

What Deep CNNs Benefit from Global Covariance Pooling: An Optimization Perspective

Recent works have demonstrated that global covariance pooling (GCP) has ...

33 Qilong Wang, et al. ∙

research

∙ 03/16/2020

Multi-Drone based Single Object Tracking with Agent Sharing Network

Drone equipped with cameras can dynamically track the target in the air ...

0 Pengfei Zhu, et al. ∙

research

∙ 01/16/2020

Vision Meets Drones: Past, Present and Future

Drones, or general UAVs, equipped with cameras have been fast deployed w...

15 Pengfei Zhu, et al. ∙

research

∙ 12/04/2019

Drone-based Joint Density Map Estimation, Localization and Tracking with Space-Time Multi-Scale Attention Network

This paper proposes a space-time multi-scale attention network (STANet) ...

0 Longyin Wen, et al. ∙

research

∙ 10/08/2019

ECA-Net: Efficient Channel Attention for Deep Convolutional Neural Networks

Channel attention has recently demonstrated to offer great potential in ...

0 Qilong Wang, et al. ∙

research

∙ 08/06/2019

Neural Blind Deconvolution Using Deep Priors

Blind deconvolution is a classical yet challenging low-level vision prob...

1 Dongwei Ren, et al. ∙

research

∙ 08/06/2019

Multi-view Deep Subspace Clustering Networks

Multi-view subspace clustering aims to discover the inherent structure b...

1 Pengfei Zhu, et al. ∙

research

∙ 01/26/2019

Progressive Image Deraining Networks: A Better and Simpler Baseline

Along with the deraining performance improvement of deep networks, their...

14 Dongwei Ren, et al. ∙

research

∙ 01/12/2019

Semi-interactive Attention Network for Answer Understanding in Reverse-QA

Question answering (QA) is an important natural language processing (NLP...

0 Qing Yin, et al. ∙

research

∙ 12/11/2018

Unsupervised Degradation Learning for Single Image Super-Resolution

Deep Convolution Neural Networks (CNN) have achieved significant perform...

8 Tianyu Zhao, et al. ∙

research

∙ 09/21/2018

SG-FCN: A Motion and Memory-Based Deep Learning Model for Video Saliency Detection

Data-driven saliency detection has attracted strong interest as a result...

14 Meijun Sun, et al. ∙

research

∙ 06/02/2018

Detecting Adversarial Examples via Key-based Network

Though deep neural networks have achieved state-of-the-art performance i...

0 Pinlong Zhao, et al. ∙

research

∙ 04/20/2018

Vision Meets Drones: A Challenge

In this paper we present a large-scale visual object detection and track...

0 Pengfei Zhu, et al. ∙

research

∙ 01/23/2014

Efficient Background Modeling Based on Sparse Representation and Outlier Iterative Removal

Background modeling is a critical component for various vision-based app...

0 Linhao Li, et al. ∙

research

∙ 09/25/2012

Feature selection with test cost constraint

Feature selection is an important preprocessing step in machine learning...

0 Fan Min, et al. ∙

Qinghua Hu

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