Z
Zhe Wu
Researcher at Chinese Academy of Sciences
Publications - 14
Citations - 1585
Zhe Wu is an academic researcher from Chinese Academy of Sciences. The author has contributed to research in topics: Feature (computer vision) & Computer science. The author has an hindex of 8, co-authored 14 publications receiving 626 citations.
Papers
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Proceedings ArticleDOI
Cascaded Partial Decoder for Fast and Accurate Salient Object Detection
Zhe Wu,Li Su,Qingming Huang +2 more
TL;DR: A novel Cascaded Partial Decoder (CPD) framework for fast and accurate salient object detection and applies the proposed framework to optimize existing multi-level feature aggregation models and significantly improve their efficiency and accuracy.
Proceedings ArticleDOI
Stacked Cross Refinement Network for Edge-Aware Salient Object Detection
Zhe Wu,Li Su,Qingming Huang +2 more
TL;DR: This framework aims to simultaneously refine multi-level features of salient object detection and edge detection by stacking Cross Refinement Unit (CRU), which outperforms existing state-of-the-art algorithms in both accuracy and efficiency.
Proceedings ArticleDOI
Label Decoupling Framework for Salient Object Detection
TL;DR: A label decoupling framework (LDF) which consists of a label decouple (LD) procedure and a feature interaction network (FIN) which outperforms state-of-the-art approaches on different evaluation metrics.
Proceedings ArticleDOI
Reverse Perspective Network for Perspective-Aware Object Counting
TL;DR: This work proposes a reverse perspective network to solve the scale variations of input images, instead of generating perspective maps to smooth final outputs, and explicitly evaluates the perspective distortions, and efficiently corrects the distortions by uniformly warping the input images.
Book ChapterDOI
Weakly-Supervised Crowd Counting Learns from Sorting Rather Than Locations
TL;DR: A weakly-supervised counting network is proposed, which directly regresses the crowd numbers without the location supervision, and a soft-label sorting network along with the counting network, which sorts the given images by their crowd numbers.