97 citations · 189 across the 18 of their papers we have counts for
18 papers
Automatically Discovering Novel Visual Categories with Self-supervised Prototype Learning
Lu Zhang, Lu Qi, Xu Yang +3
This paper tackles the problem of novel category discovery (NCD), which aims to discriminate unknown categories in large-scale image collections. The NCD task is challenging due to…
Zero-shot object goal visual navigation
Qianfan Zhao, Lu Zhang, Bin He +2
Object goal visual navigation is a challenging task that aims to guide a robot to find the target object based on its visual observation, and the target is limited to the classes p…
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…
Unseen Object Instance Segmentation with Fully Test-time RGB-D Embeddings Adaptation
Lu Zhang, Siqi Zhang, Xu Yang +2
Segmenting unseen objects is a crucial ability for the robot since it may encounter new environments during the operation. Recently, a popular solution is leveraging RGB-D features…
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…
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…
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…
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…
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…
Effective Deterministic Initialization for -Means-Like Methods via Local Density Peaks Searching
Fengfu Li, Hong Qiao, Bo Zhang
The -means clustering algorithm is popular but has the following main drawbacks: 1) the number of clusters, , needs to be provided by the user in advance, 2) it can easily re…
Poisson Noise Reduction with Higher-order Natural Image Prior Model
Wensen Feng, Hong Qiao, Yunjin Chen
Poisson denoising is an essential issue for various imaging applications, such as night vision, medical imaging and microscopy. State-of-the-art approaches are clearly dominated by…
A New Manifold Distance Measure for Visual Object Categorization
Fengfu Li, Xiayuan Huang, Hong Qiao +1
Manifold distances are very effective tools for visual object recognition. However, most of the traditional manifold distances between images are based on the pixel-level compariso…
A Weighted Common Subgraph Matching Algorithm
Xu Yang, Hong Qiao, Zhi-Yong Liu
We propose a weighted common subgraph (WCS) matching algorithm to find the most similar subgraphs in two labeled weighted graphs. WCS matching, as a natural generalization of the e…
A higher-order MRF based variational model for multiplicative noise reduction
Yunjin Chen, Wensen Feng, René Ranftl +2
The Fields of Experts (FoE) image prior model, a filter-based higher-order Markov Random Fields (MRF) model, has been shown to be effective for many image restoration problems. Mot…
GNCGCP - Graduated NonConvexity and Graduated Concavity Procedure
Zhi-Yong Liu, Hong Qiao
In this paper we propose the Graduated NonConvexity and Graduated Concavity Procedure (GNCGCP) as a general optimization framework to approximately solve the combinatorial optimiza…
Intrinsic dimension estimation of data by principal component analysis
Mingyu Fan, Nannan Gu, Hong Qiao +1
Estimating intrinsic dimensionality of data is a classic problem in pattern recognition and statistics. Principal Component Analysis (PCA) is a powerful tool in discovering dimensi…
An Explicit Nonlinear Mapping for Manifold Learning
Hong Qiao, Peng Zhang, Di Wang +1
Manifold learning is a hot research topic in the field of computer science and has many applications in the real world. A main drawback of manifold learning methods is, however, th…
Isometric Multi-Manifolds Learning
Mingyu Fan, Hong Qiao, Bo Zhang
Isometric feature mapping (Isomap) is a promising manifold learning method. However, Isomap fails to work on data which distribute on clusters in a single manifold or manifolds. Ma…