235 citations · 414 across the 12 of their papers we have counts for
12 papers
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…
Attentional Feature Refinement and Alignment Network for Aircraft Detection in SAR Imagery
Yan Zhao, Lingjun Zhao, Zhong Liu +3
Aircraft detection in Synthetic Aperture Radar (SAR) imagery is a challenging task in SAR Automatic Target Recognition (SAR ATR) areas due to aircraft's extremely discrete appearan…
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…
Multi-modal Entity Alignment in Hyperbolic Space
Hao Guo, Jiuyang Tang, Weixin Zeng +2
Many AI-related tasks involve the interactions of data in multiple modalities. It has been a new trend to merge multi-modal information into knowledge graph(KG), resulting in multi…
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…
Deep Learning for 3D Point Clouds: A Survey
Yulan Guo, Hanyun Wang, Qingyong Hu +3
Point cloud learning has lately attracted increasing attention due to its wide applications in many areas, such as computer vision, autonomous driving, and robotics. As a dominatin…
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…