no code implementations • 15 Apr 2024 • Qiangqiang Wu, Antoni B. Chan
In this paper, we propose to learn tracking representations from single point annotations (i. e., 4. 5x faster to annotate than the traditional bounding box) in a weakly supervised manner.
no code implementations • 27 Feb 2024 • Jia Wan, Qiangqiang Wu, Wei Lin, Antoni B. Chan
The existing crowd counting models require extensive training data, which is time-consuming to annotate.
no code implementations • ICCV 2023 • Qiangqiang Wu, Tianyu Yang, Wei Wu, Antoni Chan
The current popular methods for video object segmentation (VOS) implement feature matching through several hand-crafted modules that separately perform feature extraction and matching.
1 code implementation • CVPR 2023 • Qiangqiang Wu, Tianyu Yang, Ziquan Liu, Baoyuan Wu, Ying Shan, Antoni B. Chan
However, we find that this simple baseline heavily relies on spatial cues while ignoring temporal relations for frame reconstruction, thus leading to sub-optimal temporal matching representations for VOT and VOS.
Ranked #1 on Visual Object Tracking on TrackingNet (AUC metric)
no code implementations • ICCV 2023 • Zhiyang Dou, Qingxuan Wu, Cheng Lin, Zeyu Cao, Qiangqiang Wu, Weilin Wan, Taku Komura, Wenping Wang
We further demonstrate the generalizability of our method on hand mesh recovery.
1 code implementation • 8 Mar 2022 • Yan Xia, Qiangqiang Wu, Wei Li, Antoni B. Chan, Uwe Stilla
Recent works on 3D single object tracking treat the task as a target-specific 3D detection task, where an off-the-shelf 3D detector is commonly employed for the tracking.
no code implementations • CVPR 2021 • Qiangqiang Wu, Jia Wan, Antoni B. Chan
In this paper, we propose a progressive unsupervised learning (PUL) framework, which entirely removes the need for annotated training videos in visual tracking.
no code implementations • 14 Feb 2020 • Haosheng Chen, David Suter, Qiangqiang Wu, Hanzi Wang
We feed the sequence of TSLTD frames to a novel Retinal Motion Regression Network (RMRNet) to perform an end-to-end 5-DoF object motion regression.
no code implementations • 13 Feb 2020 • Haosheng Chen, Qiangqiang Wu, Yanjie Liang, Xinbo Gao, Hanzi Wang
To achieve this goal, we present an Adaptive Time-Surface with Linear Time Decay (ATSLTD) event-to-frame conversion algorithm, which asynchronously and effectively warps the spatio-temporal information of asynchronous retinal events to a sequence of ATSLTD frames with clear object contours.
no code implementations • 17 Jun 2019 • Qiangqiang Wu, Zhihui Chen, Lin Cheng, Yan Yan, Bo Li, Hanzi Wang
Incorporating such an ability to hallucinate diverse new samples of the tracked instance can help the trackers alleviate the over-fitting problem in the low-data tracking regime.
no code implementations • 6 Nov 2018 • Qiangqiang Wu, Yan Yan, Yanjie Liang, Yi Liu, Hanzi Wang
In recent years, Discriminative Correlation Filter (DCF) based tracking methods have achieved great success in visual tracking.