K
Karlekar Jayashree
Researcher at Panasonic
Publications - 8
Citations - 773
Karlekar Jayashree is an academic researcher from Panasonic. The author has contributed to research in topics: Facial recognition system & Convolutional neural network. The author has an hindex of 8, co-authored 8 publications receiving 570 citations.
Papers
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Proceedings ArticleDOI
Towards Pose Invariant Face Recognition in the Wild
Jian Zhao,Yu Cheng,Yan Xu,Lin Xiong,Jianshu Li,Fang Zhao,Karlekar Jayashree,Sugiri Pranata,Sheng Mei Shen,Junliang Xing,Shuicheng Yan,Jiashi Feng +11 more
TL;DR: Qualitative and quantitative experiments on both controlled and in-the-wild benchmarks demonstrate the superiority of the proposed Pose Invariant Model for face recognition in the wild over the state of thearts.
Proceedings ArticleDOI
Neural Person Search Machines
Hao Liu,Jiashi Feng,Zequn Jie,Karlekar Jayashree,Bo Zhao,Meibin Qi,Jianguo Jiang,Shuicheng Yan +7 more
TL;DR: Zhang et al. as mentioned in this paper proposed to recursively shrink the search area from the whole image till achieving precise localization of the target person, by fully exploiting information from the query and contextual cues in every recursive search step.
Journal ArticleDOI
Video-Based Person Re-Identification With Accumulative Motion Context
TL;DR: Wang et al. as discussed by the authors proposed an accumulative motion context (AMOC) network for video-based person re-identification, which jointly learns appearance representation and motion context from a collection of adjacent frames using a two-stream convolutional architecture.
Proceedings ArticleDOI
Conditional Convolutional Neural Network for Modality-Aware Face Recognition
TL;DR: A conditional Convolutional Neural Network, named as c-CNN, is proposed to handle multimodal face recognition via incorporating the conditional routing of the decision tree, which is evaluated with two problems of multimodality - multi-view face identification and occluded face verification.
Posted Content
Neural Person Search Machines
Hao Liu,Jiashi Feng,Zequn Jie,Karlekar Jayashree,Bo Zhao,Meibin Qi,Jianguo Jiang,Shuicheng Yan +7 more
TL;DR: Evaluations on two benchmark datasets have demonstrated that the Neural Person Search Machines (NPSM) developed can outperform current state-of-the-arts in both mAP and top-1 evaluation protocols.