no code implementations • 17 Mar 2024 • Guangze Zheng, ShiJie Lin, Haobo Zuo, Changhong Fu, Jia Pan
Most methods that solely depend on coarse-grained object cues, such as boxes and the overall appearance of the object, are susceptible to degradation due to distorted internal relationships of dynamic objects.
1 code implementation • 20 Aug 2023 • Ziang Cao, Ziyuan Huang, Liang Pan, Shiwei Zhang, Ziwei Liu, Changhong Fu
To handle those problems, we propose a two-level framework (TCTrack) that can exploit temporal contexts efficiently.
1 code implementation • 3 Jul 2023 • Changhong Fu, Liangliang Yao, Haobo Zuo, Guangze Zheng, Jia Pan
However, the state-of-the-art (SOTA) DA still lacks the potential object with accurate pixel-level location and boundary to generate the high-quality target domain training sample.
1 code implementation • 20 Mar 2023 • Junjie Ye, Changhong Fu, Ziang Cao, Shan An, Guangze Zheng, Bowen Li
To realize reliable UAV tracking at night, a spatial-channel Transformer-based low-light enhancer (namely SCT), which is trained in a novel task-inspired manner, is proposed and plugged prior to tracking approaches.
1 code implementation • 8 Mar 2023 • Liangliang Yao, Changhong Fu, Sihang Li, Guangze Zheng, Junjie Ye
The proposed method designs a new task-specific object saliency mining network to refine the cross-correlation operation and effectively discriminate foreground and background information.
1 code implementation • 8 Mar 2023 • Changhong Fu, Mutian Cai, Sihang Li, Kunhan Lu, Haobo Zuo, Chongjun Liu
To address the above issues, this work proposes a novel framework with continuity-aware latent interframe information mining for reliable UAV tracking, i. e., ClimRT.
1 code implementation • 26 Nov 2022 • Guangze Zheng, Changhong Fu, Junjie Ye, Bowen Li, Geng Lu, Jia Pan
The key to the visual UAM approaching lies in object tracking, while current UAM tracking typically relies on costly model-based methods.
1 code implementation • ICCV 2023 • Bowen Li, Ziyuan Huang, Junjie Ye, Yiming Li, Sebastian Scherer, Hang Zhao, Changhong Fu
Visual object tracking is essential to intelligent robots.
1 code implementation • 14 Aug 2022 • Changhong Fu, Haolin Dong, Junjie Ye, Guangze Zheng, Sihang Li, Jilin Zhao
Pixel-level range mask is introduced to make HighlightNet more focused on the enhancement of the tracking object and regions without light sources.
1 code implementation • 1 Aug 2022 • Changhong Fu, Weiyu Peng, Sihang Li, Junjie Ye, Ziang Cao
Specifically, with local-modeling to global-search mechanism, the proposed tracker replaces the global encoder by a novel local-recognition encoder.
1 code implementation • 9 May 2022 • Changhong Fu, Kunhan Lu, Guangze Zheng, Junjie Ye, Ziang Cao, Bowen Li, Geng Lu
Unmanned aerial vehicle (UAV)-based visual object tracking has enabled a wide range of applications and attracted increasing attention in the field of intelligent transportation systems because of its versatility and effectiveness.
2 code implementations • CVPR 2022 • Junjie Ye, Changhong Fu, Guangze Zheng, Danda Pani Paudel, Guang Chen
Previous advances in object tracking mostly reported on favorable illumination circumstances while neglecting performance at nighttime, which significantly impeded the development of related aerial robot applications.
1 code implementation • 3 Mar 2022 • Changhong Fu, Sihang Li, Xinnan Yuan, Junjie Ye, Ziang Cao, Fangqiang Ding
Therefore, to help increase awareness of the potential risk and the robustness of UAV tracking, this work proposes a novel adaptive adversarial attack approach, i. e., Ad$^2$Attack, against UAV object tracking.
1 code implementation • CVPR 2022 • Ziang Cao, Ziyuan Huang, Liang Pan, Shiwei Zhang, Ziwei Liu, Changhong Fu
Temporal contexts among consecutive frames are far from being fully utilized in existing visual trackers.
1 code implementation • 24 Aug 2021 • Shan An, Fangru Zhou, Mei Yang, Haogang Zhu, Changhong Fu, Konstantinos A. Tsintotas
Estimating a scene's depth to achieve collision avoidance against moving pedestrians is a crucial and fundamental problem in the robotic field.
1 code implementation • ICCV 2021 • Ziang Cao, Changhong Fu, Junjie Ye, Bowen Li, Yiming Li
Most existing Siamese-based tracking methods execute the classification and regression of the target object based on the similarity maps.
1 code implementation • 30 Jul 2021 • Junjie Ye, Changhong Fu, Guangze Zheng, Ziang Cao, Bowen Li
Recent years have witnessed the fast evolution and promising performance of the convolutional neural network (CNN)-based trackers, which aim at imitating biological visual systems.
1 code implementation • 16 Jun 2021 • Ziang Cao, Changhong Fu, Junjie Ye, Bowen Li, Yiming Li
By virtue of the attention mechanism, we conduct a special attentional aggregation network (AAN) consisting of self-AAN and cross-AAN for raising the representation ability of features eventually.
1 code implementation • 15 Jun 2021 • Guangze Zheng, Changhong Fu, Junjie Ye, Fuling Lin, Fangqiang Ding
However, prevalent discriminative correlation filter (DCF) based trackers are insensitive to target mutations due to a predefined label, which concentrates on merely the centre of the training region.
1 code implementation • 4 Jun 2021 • Bowen Li, Changhong Fu, Fangqiang Ding, Junjie Ye, Fuling Lin
The target-aware mask can be applied to jointly train a target-focused filter that assists the context filter for robust tracking.
2 code implementations • 8 Mar 2021 • Bowen Li, Yiming Li, Junjie Ye, Changhong Fu, Hang Zhao
As a crucial robotic perception capability, visual tracking has been intensively studied recently.
1 code implementation • 21 Jan 2021 • Bowen Li, Changhong Fu, Fangqiang Ding, Junjie Ye, Fuling Lin
However, prior tracking methods have merely focused on robust tracking in the well-illuminated scenes, while ignoring trackers' capabilities to be deployed in the dark.
1 code implementation • 19 Dec 2020 • Changhong Fu, Ziang Cao, Yiming Li, Junjie Ye, Chen Feng
In the domain of visual tracking, most deep learning-based trackers highlight the accuracy but casting aside efficiency.
1 code implementation • 13 Oct 2020 • Changhong Fu, Bowen Li, Fangqiang Ding, Fuling Lin, Geng Lu
Aerial tracking, which has exhibited its omnipresent dedication and splendid performance, is one of the most active applications in the remote sensing field.
1 code implementation • 10 Aug 2020 • Changhong Fu, Fangqiang Ding, Yiming Li, Jin Jin, Chen Feng
By repressing the response of distractors in the regressor learning, we can dynamically and adaptively alter our regression target to leverage the tracking robustness as well as adaptivity.
1 code implementation • 10 Aug 2020 • Fangqiang Ding, Changhong Fu, Yiming Li, Jin Jin, Chen Feng
Current unmanned aerial vehicle (UAV) visual tracking algorithms are primarily limited with respect to: (i) the kind of size variation they can deal with, (ii) the implementation speed which hardly meets the real-time requirement.
no code implementations • 9 Aug 2020 • Changhong Fu, Xiaoxiao Yang, Fan Li, Juntao Xu, Changjing Liu, Peng Lu
By minimizing the difference between the practical and the scheduled ideal consistency map, the consistency level is constrained to maintain temporal smoothness, and rich temporal information contained in response maps is introduced.
1 code implementation • 2 Aug 2020 • Yujie He, Changhong Fu, Fuling Lin, Yiming Li, Peng Lu
Object tracking has been broadly applied in unmanned aerial vehicle (UAV) tasks in recent years.
1 code implementation • CVPR 2020 • Yiming Li, Changhong Fu, Fangqiang Ding, Ziyuan Huang, Geng Lu
Considerable tests in the indoor practical scenarios have proven the effectiveness and versatility of our localization method.
1 code implementation • 11 Mar 2020 • Yiming Li, Changhong Fu, Ziyuan Huang, Yinqiang Zhang, Jia Pan
Correlation filter-based tracking has been widely applied in unmanned aerial vehicle (UAV) with high efficiency.
1 code implementation • 11 Mar 2020 • Fan Li, Changhong Fu, Fuling Lin, Yiming Li, Peng Lu
After the establishment of a new slot, the weighted fusion of the previous samples generates one key-sample, in order to reduce the number of samples to be scored.
1 code implementation • 24 Sep 2019 • Yiming Li, Changhong Fu, Fangqiang Ding, Ziyuan Huang, Jia Pan
The outstanding computational efficiency of discriminative correlation filter (DCF) fades away with various complicated improvements.
1 code implementation • 10 Aug 2019 • Changhong Fu, Ziyuan Huang, Yiming Li, Ran Duan, Peng Lu
Meanwhile, convolutional features are extracted to provide a more comprehensive representation of the object.
1 code implementation • ICCV 2019 • Ziyuan Huang, Changhong Fu, Yiming Li, Fuling Lin, Peng Lu
Traditional framework of discriminative correlation filters (DCF) is often subject to undesired boundary effects.
no code implementations • 6 Dec 2017 • Guang Chen, Shu Liu, Kejia Ren, Zhongnan Qu, Changhong Fu, Gereon Hinz, Alois Knoll
However, the mobile sensing perception brings new challenges for how to efficiently analyze and intelligently interpret the deluge of IoT data in mission- critical services.