activity
20172023
most citedAmulet: Aggregating Multi-level Convolutional Features for Salient Object Detection

116 citations · 412 across the 21 of their papers we have counts for

collaborators

21 papers

quant-ph2023★ 3 cited

Quantum secured LiDAR with Gaussian modulated coherent states

Dong Wang, Juan-Ying Zhao, Ya-Chao Wang +2

LiDAR systems that rely on classical signals are susceptible to intercept-and-recent spoofing attacks, where a target attempts to avoid detection. To address this vulnerability, we…

cs.CV2023★ 6 cited

Exploring Lightweight Hierarchical Vision Transformers for Efficient Visual Tracking

Ben Kang, Xin Chen, Dong Wang +2

Transformer-based visual trackers have demonstrated significant progress owing to their superior modeling capabilities. However, existing trackers are hampered by low speed, limiti…

cs.CV2023★ 6 cited

Hybrid-SORT: Weak Cues Matter for Online Multi-Object Tracking

Mingzhan Yang, Guangxin Han, Bin Yan +4

Multi-Object Tracking (MOT) aims to detect and associate all desired objects across frames. Most methods accomplish the task by explicitly or implicitly leveraging strong cues (i.e…

cs.CV2023

Neural Image Re-Exposure

Xinyu Zhang, Hefei Huang, Xu Jia +2

The shutter strategy applied to the photo-shooting process has a significant influence on the quality of the captured photograph. An improper shutter may lead to a blurry image, vi…

cs.CV2023★ 1 cited

Visual Prompt Multi-Modal Tracking

Jiawen Zhu, Simiao Lai, Xin Chen +2

Visible-modal object tracking gives rise to a series of downstream multi-modal tracking tributaries. To inherit the powerful representations of the foundation model, a natural modu…

cs.CV2023★ 2 cited

Dual Memory Aggregation Network for Event-Based Object Detection with Learnable Representation

Dongsheng Wang, Xu Jia, Yang Zhang +5

Event-based cameras are bio-inspired sensors that capture brightness change of every pixel in an asynchronous manner. Compared with frame-based sensors, event cameras have microsec…

cs.CV2023★ 5 cited

Universal Instance Perception as Object Discovery and Retrieval

Bin Yan, Yi Jiang, Jiannan Wu +4

All instance perception tasks aim at finding certain objects specified by some queries such as category names, language expressions, and target annotations, but this complete field…

cs.CV2022

Towards Grand Unification of Object Tracking

Bin Yan, Yi Jiang, Peize Sun +4

We present a unified method, termed Unicorn, that can simultaneously solve four tracking problems (SOT, MOT, VOS, MOTS) with a single network using the same model parameters. Due t…

cs.CV2022★ 2 cited

SRRT: Exploring Search Region Regulation for Visual Object Tracking

Jiawen Zhu, Xin Chen, Pengyu Zhang +4

The dominant trackers generate a fixed-size rectangular region based on the previous prediction or initial bounding box as the model input, i.e., search region. While this manner o…

cs.CV2022★ 9 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.CV2022★ 2 cited

Efficient Visual Tracking via Hierarchical Cross-Attention Transformer

Xin Chen, Ben Kang, Dong Wang +2

In recent years, target tracking has made great progress in accuracy. This development is mainly attributed to powerful networks (such as transformers) and additional modules (such…

cs.CV2022★ 1 cited

High-Performance Transformer Tracking

Xin Chen, Bin Yan, Jiawen Zhu +3

Correlation has a critical role in the tracking field, especially in recent popular Siamese-based trackers. The correlation operation is a simple fusion method that considers the s…

physics.app-ph2022

Overcoming Van der Waals Forces in reconfigurable nanostructures

Wang Zhang, Hao Wang, Alvin T. L. Tan +11

Reconfigurable metamaterials require constituent nanostructures to demonstrate switching of shapes with external stimuli. For generality, such nanostructures would touch and stick…

physics.data-an2019★ 12 cited

Timing and characterization of shaped pulses with MHz ADCs in a detector system: a comparative study and deep learning approach

Pengcheng Ai, Dong Wang, Guangming Huang +3

Timing systems based on Analog-to-Digital Converters are widely used in the design of previous high energy physics detectors. In this paper, we propose a new method based on deep l…

cs.CV2018★ 73 cited

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★ 9 cited

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★ 110 cited

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★ 20 cited

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★ 12 cited

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…

cs.CV2017★ 23 cited

Learning Uncertain Convolutional Features for Accurate Saliency Detection

Pingping Zhang, Dong Wang, Huchuan Lu +2

Deep convolutional neural networks (CNNs) have delivered superior performance in many computer vision tasks. In this paper, we propose a novel deep fully convolutional network mode…

cs.CV2017★ 116 cited

Amulet: Aggregating Multi-level Convolutional Features for Salient Object Detection

Pingping Zhang, Dong Wang, Huchuan Lu +2

Fully convolutional neural networks (FCNs) have shown outstanding performance in many dense labeling problems. One key pillar of these successes is mining relevant information from…