324 citations · 773 across the 23 of their papers we have counts for
23 papers
Few-shot Class-incremental Learning for Classification and Object Detection: A Survey
Jinghua Zhang, Li Liu, Olli Silvén +2
Few-shot Class-Incremental Learning (FSCIL) presents a unique challenge in Machine Learning (ML), as it necessitates the Incremental Learning (IL) of new classes from sparsely labe…
Deep Learning for Visual Speech Analysis: A Survey
Changchong Sheng, Gangyao Kuang, Liang Bai +5
Visual speech, referring to the visual domain of speech, has attracted increasing attention due to its wide applications, such as public security, medical treatment, military defen…
Challenges of Artificial Intelligence -- From Machine Learning and Computer Vision to Emotional Intelligence
Matti Pietikäinen, Olli Silven
Artificial intelligence (AI) has become a part of everyday conversation and our lives. It is considered as the new electricity that is revolutionizing the world. AI is heavily inve…
Dynamic Binary Neural Network by learning channel-wise thresholds
Jiehua Zhang, Zhuo Su, Yanghe Feng +3
Binary neural networks (BNNs) constrain weights and activations to +1 or -1 with limited storage and computational cost, which is hardware-friendly for portable devices. Recently,…
Pixel Difference Networks for Efficient Edge Detection
Zhuo Su, Wenzhe Liu, Zitong Yu +5
Recently, deep Convolutional Neural Networks (CNNs) can achieve human-level performance in edge detection with the rich and abstract edge representation capacities. However, the hi…
Deep Learning for Scene Classification: A Survey
Delu Zeng, Minyu Liao, Mohammad Tavakolian +5
Scene classification, aiming at classifying a scene image to one of the predefined scene categories by comprehending the entire image, is a longstanding, fundamental and challengin…
FTBNN: Rethinking Non-linearity for 1-bit CNNs and Going Beyond
Zhuo Su, Linpu Fang, Deke Guo +3
Binary neural networks (BNNs), where both weights and activations are binarized into 1 bit, have been widely studied in recent years due to its great benefit of highly accelerated…
Dynamic Group Convolution for Accelerating Convolutional Neural Networks
Zhuo Su, Linpu Fang, Wenxiong Kang +3
Replacing normal convolutions with group convolutions can significantly increase the computational efficiency of modern deep convolutional networks, which has been widely adopted i…
Extended Local Binary Patterns for Efficient and Robust Spontaneous Facial Micro-Expression Recognition
Chengyu Guo, Jingyun Liang, Geng Zhan +3
Facial Micro-Expressions (MEs) are spontaneous, involuntary facial movements when a person experiences an emotion but deliberately or unconsciously attempts to conceal his or her g…
A Global Alignment Kernel based Approach for Group-level Happiness Intensity Estimation
Xiaohua Huang, Abhinav Dhall, Roland Goecke +2
With the progress in automatic human behavior understanding, analysing the perceived affect of multiple people has been recieved interest in affective computing community. Unlike c…
Deep Learning for Generic Object Detection: A Survey
Li Liu, Wanli Ouyang, Xiaogang Wang +4
Object detection, one of the most fundamental and challenging problems in computer vision, seeks to locate object instances from a large number of predefined categories in natural…
Texture Classification in Extreme Scale Variations using GANet
Li Liu, Jie Chen, Guoying Zhao +3
Research in texture recognition often concentrates on recognizing textures with intraclass variations such as illumination, rotation, viewpoint and small scale changes. In contrast…
From BoW to CNN: Two Decades of Texture Representation for Texture Classification
Li Liu, Jie Chen, Paul Fieguth +3
Texture is a fundamental characteristic of many types of images, and texture representation is one of the essential and challenging problems in computer vision and pattern recognit…
PCANet-II: When PCANet Meets the Second Order Pooling
Lei Tian, Xiaopeng Hong, Guoying Zhao +3
PCANet, as one noticeable shallow network, employs the histogram representation for feature pooling. However, there are three main problems about this kind of pooling method. First…
Two decades of local binary patterns: A survey
Matti Pietikäinen, Guoying Zhao
Texture is an important characteristic for many types of images. In recent years very discriminative and computationally efficient local texture descriptors based on local binary p…
Analyzing the Affect of a Group of People Using Multi-modal Framework
Xiaohua Huang, Abhinav Dhall, Xin Liu +4
Millions of images on the web enable us to explore images from social events such as a family party, thus it is of interest to understand and model the affect exhibited by a group…
Spontaneous Facial Micro-Expression Recognition using Discriminative Spatiotemporal Local Binary Pattern with an Improved Integral Projection
Xiaohua Huang, Sujing Wang, Xin Liu +3
Recently, there are increasing interests in inferring mirco-expression from facial image sequences. Due to subtle facial movement of micro-expressions, feature extraction has becom…
Probing the Intra-Component Correlations within Fisher Vector for Material Classification
Xiaopeng Hong, Xianbiao Qi, Guoying Zhao +1
Fisher vector (FV) has become a popular image representation. One notable underlying assumption of the FV framework is that local descriptors are well decorrelated within each clus…
Towards Reading Hidden Emotions: A comparative Study of Spontaneous Micro-expression Spotting and Recognition Methods
Xiaobai Li, Xiaopeng Hong, Antti Moilanen +4
Micro-expressions (MEs) are rapid, involuntary facial expressions which reveal emotions that people do not intend to show. Studying MEs is valuable as recognizing them has many imp…
HEp-2 Cell Classification: The Role of Gaussian Scale Space Theory as A Pre-processing Approach
Xianbiao Qi, Guoying Zhao, Jie Chen +1
\textit{Indirect Immunofluorescence Imaging of Human Epithelial Type 2} (HEp-2) cells is an effective way to identify the presence of Anti-Nuclear Antibody (ANA). Most existing wor…
LOAD: Local Orientation Adaptive Descriptor for Texture and Material Classification
Xianbiao Qi, Guoying Zhao, Linlin Shen +2
In this paper, we propose a novel local feature, called Local Orientation Adaptive Descriptor (LOAD), to capture regional texture in an image. In LOAD, we proposed to define point…
HEp-2 Cell Classification via Fusing Texture and Shape Information
Xianbiao Qi, Guoying Zhao, Chun-Guang Li +2
Indirect Immunofluorescence (IIF) HEp-2 cell image is an effective evidence for diagnosis of autoimmune diseases. Recently computer-aided diagnosis of autoimmune diseases by IIF HE…
Dynamic texture and scene classification by transferring deep image features
Xianbiao Qi, Chun-Guang Li, Guoying Zhao +2
Dynamic texture and scene classification are two fundamental problems in understanding natural video content. Extracting robust and effective features is a crucial step towards sol…