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20172022
most citedAmulet: Aggregating Multi-level Convolutional Features for Salient Object Detection

116 citations · 160 across the 5 of their papers we have counts for

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8 papers · 1 filter

cs.CV20229 cited

Visible-Thermal UAV Tracking: A Large-Scale Benchmark and New Baseline

Pengyu Zhang, Jie Zhao, Dong Wang +2

With the popularity of multi-modal sensors, visible-thermal (RGB-T) object tracking is to achieve robust performance and wider application scenarios with the guidance of objects' t…

cs.CV2018

Learning regression and verification networks for long-term visual tracking

Yunhua Zhang, Dong Wang, Lijun Wang +2

Compared with short-term tracking, the long-term tracking task requires determining the tracked object is present or absent, and then estimating the accurate bounding box if presen…

cs.CV2018

Correlation Tracking via Joint Discrimination and Reliability Learning

Chong Sun, Dong Wang, Huchuan Lu +1

For visual tracking, an ideal filter learned by the correlation filter (CF) method should take both discrimination and reliability information. However, existing attempts usually f…

cs.CV2018

Video Person Re-identification by Temporal Residual Learning

Ju Dai, Pingping Zhang, Huchuan Lu +1

In this paper, we propose a novel feature learning framework for video person re-identification (re-ID). The proposed framework largely aims to exploit the adequate temporal inform…

cs.CV2018

Agile Amulet: Real-Time Salient Object Detection with Contextual Attention

Pingping Zhang, Luyao Wang, Dong Wang +2

This paper proposes an Agile Aggregating Multi-Level feaTure framework (Agile Amulet) for salient object detection. The Agile Amulet builds on previous works to predict saliency ma…

cs.CV2018

Non-rigid Object Tracking via Deep Multi-scale Spatial-temporal Discriminative Saliency Maps

Pingping Zhang, Wei Liu, Dong Wang +4

In this paper, we propose a novel effective non-rigid object tracking framework based on the spatial-temporal consistent saliency detection. In contrast to most existing trackers t…