activity
20182022
most citedMaximum Density Divergence for Domain Adaptation

343 citations · 372 across the 4 of their papers we have counts for

collaborators

7 papers

cs.CV2020

Patch-wise Attack for Fooling Deep Neural Network

Lianli Gao, Qilong Zhang, Jingkuan Song +2

By adding human-imperceptible noise to clean images, the resultant adversarial examples can fool other unknown models. Features of a pixel extracted by deep neural networks (DNNs)…

cs.CV202021 cited

Improving Target-driven Visual Navigation with Attention on 3D Spatial Relationships

Yunlian Lv, Ning Xie, Yimin Shi +2

Embodied artificial intelligence (AI) tasks shift from tasks focusing on internet images to active settings involving embodied agents that perceive and act within 3D environments.…

cs.CV2020343 cited

Maximum Density Divergence for Domain Adaptation

Li Jingjing, Chen Erpeng, Ding Zhengming +3

Unsupervised domain adaptation addresses the problem of transferring knowledge from a well-labeled source domain to an unlabeled target domain where the two domains have distinctiv…

cs.CV2019

MetaMixUp: Learning Adaptive Interpolation Policy of MixUp with Meta-Learning

Zhijun Mai, Guosheng Hu, Dexiong Chen +2

MixUp is an effective data augmentation method to regularize deep neural networks via random linear interpolations between pairs of samples and their labels. It plays an important…

cs.CV2019

Temporal Reasoning Graph for Activity Recognition

Jingran Zhang, Fumin Shen, Xing Xu +1

Despite great success has been achieved in activity analysis, it still has many challenges. Most existing work in activity recognition pay more attention to design efficient archit…

cs.CV20193 cited

Locality Preserving Joint Transfer for Domain Adaptation

Li Jingjing, Jing Mengmeng, Lu Ke +2

Domain adaptation aims to leverage knowledge from a well-labeled source domain to a poorly-labeled target domain. A majority of existing works transfer the knowledge at either feat…