1.1k citations · 5.1k across the 81 of their papers we have counts for
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Dense Multimodal Fusion for Hierarchically Joint Representation
Di Hu, Feiping Nie, Xuelong Li
Multiple modalities can provide more valuable information than single one by describing the same contents in various ways. Hence, it is highly expected to learn effective joint rep…
Deep LDA Hashing
Di Hu, Feiping Nie, Xuelong Li
The conventional supervised hashing methods based on classification do not entirely meet the requirements of hashing technique, but Linear Discriminant Analysis (LDA) does. In this…
Triply Supervised Decoder Networks for Joint Detection and Segmentation
Jiale Cao, Yanwei Pang, Xuelong Li
Joint object detection and semantic segmentation can be applied to many fields, such as self-driving cars and unmanned surface vessels. An initial and important progress towards th…
Deep Smoke Segmentation
Feiniu Yuan, Lin Zhang, Xue Xia +3
Inspired by the recent success of fully convolutional networks (FCN) in semantic segmentation, we propose a deep smoke segmentation network to infer high quality segmentation masks…
TLR: Transfer Latent Representation for Unsupervised Domain Adaptation
Pan Xiao, Bo Du, Jia Wu +3
Domain adaptation refers to the process of learning prediction models in a target domain by making use of data from a source domain. Many classic methods solve the domain adaptatio…
Low Rank Regularization: A Review
Zhanxuan Hu, Feiping Nie, Rong Wang +1
Low rank regularization, in essence, involves introducing a low rank or approximately low rank assumption for matrix we aim to learn, which has achieved great success in many field…
Deep Multimodal Clustering for Unsupervised Audiovisual Learning
Di Hu, Feiping Nie, Xuelong Li
The seen birds twitter, the running cars accompany with noise, etc. These naturally audiovisual correspondences provide the possibilities to explore and understand the outside worl…
Exploring Multi-Branch and High-Level Semantic Networks for Improving Pedestrian Detection
Jiale Cao, Yanwei Pang, Xuelong Li
To better detect pedestrians of various scales, deep multi-scale methods usually detect pedestrians of different scales by different in-network layers. However, the semantic levels…
PixelLink: Detecting Scene Text via Instance Segmentation
Dan Deng, Haifeng Liu, Xuelong Li +1
Most state-of-the-art scene text detection algorithms are deep learning based methods that depend on bounding box regression and perform at least two kinds of predictions: text/non…