27 citations · 51 across the 8 of their papers we have counts for
8 papers
M2P: Improving Visual Foundation Models with Mask-to-Point Weakly-Supervised Learning for Dense Point Tracking
Qiangqiang Wu, Tianyu Yang, Bo Fang +4
Tracking Any Point (TAP) has emerged as a fundamental tool for video understanding. Current approaches adapt Vision Foundation Models (VFMs) like DINOv2 via offline finetuning or t…
Scalable Video Object Segmentation with Simplified Framework
Qiangqiang Wu, Tianyu Yang, Wei WU +1
The current popular methods for video object segmentation (VOS) implement feature matching through several hand-crafted modules that separately perform feature extraction and match…
DropMAE: Learning Representations via Masked Autoencoders with Spatial-Attention Dropout for Temporal Matching Tasks
Qiangqiang Wu, Tianyu Yang, Ziquan Liu +3
This paper studies masked autoencoder (MAE) video pre-training for various temporal matching-based downstream tasks, i.e., object-level tracking tasks including video object tracki…
A Lightweight and Detector-free 3D Single Object Tracker on Point Clouds
Yan Xia, Qiangqiang Wu, Wei Li +2
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. However,…
ROAM: Recurrently Optimizing Tracking Model
Tianyu Yang, Pengfei Xu, Runbo Hu +2
In this paper, we design a tracking model consisting of response generation and bounding box regression, where the first component produces a heat map to indicate the presence of t…
Visual Tracking via Dynamic Memory Networks
Tianyu Yang, Antoni B. Chan
Template-matching methods for visual tracking have gained popularity recently due to their good performance and fast speed. However, they lack effective ways to adapt to changes in…
Learning Dynamic Memory Networks for Object Tracking
Tianyu Yang, Antoni B. Chan
Template-matching methods for visual tracking have gained popularity recently due to their comparable performance and fast speed. However, they lack effective ways to adapt to chan…
Recurrent Filter Learning for Visual Tracking
Tianyu Yang, Antoni B. Chan
Recently using convolutional neural networks (CNNs) has gained popularity in visual tracking, due to its robust feature representation of images. Recent methods perform online trac…