377 citations · 2k across the 95 of their papers we have counts for
18 papers · 1 filter
1st Place Solution to VisDA-2020: Bias Elimination for Domain Adaptive Pedestrian Re-identification
Jianyang Gu, Hao Luo, Weihua Chen +6
This paper presents our proposed methods for domain adaptive pedestrian re-identification (Re-ID) task in Visual Domain Adaptation Challenge (VisDA-2020). Considering the large gap…
Blurring Fools the Network -- Adversarial Attacks by Feature Peak Suppression and Gaussian Blurring
Chenchen Zhao, Hao Li
Existing pixel-level adversarial attacks on neural networks may be deficient in real scenarios, since pixel-level changes on the data cannot be fully delivered to the neural networ…
Amplifying the Anterior-Posterior Difference via Data Enhancement -- A More Robust Deep Monocular Orientation Estimation Solution
Chenchen Zhao, Hao Li
Existing deep-learning based monocular orientation estimation algorithms faces the problem of confusion between the anterior and posterior parts of the objects, caused by the featu…
Exploiting Vulnerability of Pooling in Convolutional Neural Networks by Strict Layer-Output Manipulation for Adversarial Attacks
Chenchen Zhao, Hao Li
Convolutional neural networks (CNN) have been more and more applied in mobile robotics such as intelligent vehicles. Security of CNNs in robotics applications is an important issue…
SGD_Tucker: A Novel Stochastic Optimization Strategy for Parallel Sparse Tucker Decomposition
Hao Li, Zixuan Li, Kenli Li +3
Sparse Tucker Decomposition (STD) algorithms learn a core tensor and a group of factor matrices to obtain an optimal low-rank representation feature for the \underline{H}igh-\under…
AU-Guided Unsupervised Domain Adaptive Facial Expression Recognition
Kai Wang, Yuxin Gu, Xiaojiang Peng +3
The domain diversities including inconsistent annotation and varied image collection conditions inevitably exist among different facial expression recognition (FER) datasets, which…
Seed the Views: Hierarchical Semantic Alignment for Contrastive Representation Learning
Haohang Xu, Xiaopeng Zhang, Hao Li +3
Self-supervised learning based on instance discrimination has shown remarkable progress. In particular, contrastive learning, which regards each image as well as its augmentations…
Heterogeneous Contrastive Learning: Encoding Spatial Information for Compact Visual Representations
Xinyue Huo, Lingxi Xie, Longhui Wei +6
Contrastive learning has achieved great success in self-supervised visual representation learning, but existing approaches mostly ignored spatial information which is often crucial…
ULSD: Unified Line Segment Detection across Pinhole, Fisheye, and Spherical Cameras
Hao Li, Huai Yu, Wen Yang +2
Line segment detection is essential for high-level tasks in computer vision and robotics. Currently, most stateof-the-art (SOTA) methods are dedicated to detecting straight line se…
Center-wise Local Image Mixture For Contrastive Representation Learning
Hao Li, Xiaopeng Zhang, Hongkai Xiong
Contrastive learning based on instance discrimination trains model to discriminate different transformations of the anchor sample from other samples, which does not consider the se…
Data Augmentation for End-to-end Code-switching Speech Recognition
Chenpeng Du, Hao Li, Yizhou Lu +2
Training a code-switching end-to-end automatic speech recognition (ASR) model normally requires a large amount of data, while code-switching data is often limited. In this paper, t…
Towards human-interpretable, automated learning of feedback control for the mixing layer
Hao Li, Guy Y. Cornejo Maceda, Yiqing Li +3
We propose an automated analysis of the flow control behaviour from an ensemble of control laws and associated time-resolved flow snapshots. The input may be the rich data base of…
Revisiting the Continuity of Rotation Representations in Neural Networks
Sitao Xiang, Hao Li
In this paper, we provide some careful analysis of certain pathological behavior of Euler angles and unit quaternions encountered in previous works related to rotation representati…
NTIRE 2020 Challenge on Real-World Image Super-Resolution: Methods and Results
Andreas Lugmayr, Martin Danelljan, Radu Timofte +43
This paper reviews the NTIRE 2020 challenge on real world super-resolution. It focuses on the participating methods and final results. The challenge addresses the real world settin…
Learning Formation of Physically-Based Face Attributes
Ruilong Li, Karl Bladin, Yajie Zhao +8
Based on a combined data set of 4000 high resolution facial scans, we introduce a non-linear morphable face model, capable of producing multifarious face geometry of pore-level res…
CSRN: Collaborative Sequential Recommendation Networks for News Retrieval
Bing Bai, Guanhua Zhang, Ye Lin +3
Nowadays, news apps have taken over the popularity of paper-based media, providing a great opportunity for personalization. Recurrent Neural Network (RNN)-based sequential recommen…
Objects detection for remote sensing images based on polar coordinates
Lin Zhou, Haoran Wei, Hao Li +3
Arbitrary-oriented object detection is an important task in the field of remote sensing object detection. Existing studies have shown that the polar coordinate system has obvious a…
Cluster-based network model
Hao Li, Daniel Fernex, Richard Semaan +3
We propose an automatable data-driven methodology for robust nonlinear reduced-order modelling from time-resolved snapshot data. In the kinematical coarse-graining, the snapshots a…