activity
20162022
most citedWeakly Aligned Feature Fusion for Multimodal Object Detection

97 citations · 120 across the 5 of their papers we have counts for

collaborators

7 papers

cs.CV202297 cited

Weakly Aligned Feature Fusion for Multimodal Object Detection

Lu Zhang, Zhiyong Liu, Xiangyu Zhu +4

To achieve accurate and robust object detection in the real-world scenario, various forms of images are incorporated, such as color, thermal, and depth. However, multimodal data of…

cs.LG20211 cited

A Minimax Probability Machine for Non-Decomposable Performance Measures

Junru Luo, Hong Qiao, Bo Zhang

Imbalanced classification tasks are widespread in many real-world applications. For such classification tasks, in comparison with the accuracy rate, it is usually much more appropr…

cs.LG2021

Learning with Smooth Hinge Losses

JunRu Luo, Hong Qiao, Bo Zhang

Due to the non-smoothness of the Hinge loss in SVM, it is difficult to obtain a faster convergence rate with modern optimization algorithms. In this paper, we introduce two smooth…

cs.CV2018

Multi-view Laplacian Eigenmaps Based on Bag-of-Neighbors For RGBD Human Emotion Recognition

Shenglan Liu, Shuai Guo, Hong Qiao +6

Human emotion recognition is an important direction in the field of biometric and information forensics. However, most existing human emotion research are based on the single RGB v…

cs.CV201716 cited

Discriminatively Boosted Image Clustering with Fully Convolutional Auto-Encoders

Fengfu Li, Hong Qiao, Bo Zhang +1

Traditional image clustering methods take a two-step approach, feature learning and clustering, sequentially. However, recent research results demonstrated that combining the separ…

cs.CV20176 cited

A Fast and Compact Saliency Score Regression Network Based on Fully Convolutional Network

Xuanyang Xi, Yongkang Luo, Fengfu Li +2

Visual saliency detection aims at identifying the most visually distinctive parts in an image, and serves as a pre-processing step for a variety of computer vision and image proces…