19 citations · 34 across the 6 of their papers we have counts for
6 papers
FMRT: Learning Accurate Feature Matching with Reconciliatory Transformer
Xinyu Zhang, Li Wang, Zhiqiang Jiang +6
Local Feature Matching, an essential component of several computer vision tasks (e.g., structure from motion and visual localization), has been effectively settled by Transformer-b…
OFVL-MS: Once for Visual Localization across Multiple Indoor Scenes
Tao Xie, Kun Dai, Siyi Lu +7
In this work, we seek to predict camera poses across scenes with a multi-task learning manner, where we view the localization of each scene as a new task. We propose OFVL-MS, a uni…
Poly-MOT: A Polyhedral Framework For 3D Multi-Object Tracking
Xiaoyu Li, Tao Xie, Dedong Liu +5
3D Multi-object tracking (MOT) empowers mobile robots to accomplish well-informed motion planning and navigation tasks by providing motion trajectories of surrounding objects. Howe…
OAMatcher: An Overlapping Areas-based Network for Accurate Local Feature Matching
Kun Dai, Tao Xie, Ke Wang +3
Local feature matching is an essential component in many visual applications. In this work, we propose OAMatcher, a Tranformer-based detector-free method that imitates humans behav…
YOWOv2: A Stronger yet Efficient Multi-level Detection Framework for Real-time Spatio-temporal Action Detection
Jianhua Yang, Kun Dai
Designing a real-time framework for the spatio-temporal action detection task is still a challenge. In this paper, we propose a novel real-time action detection framework, YOWOv2.…
DeepMatcher: A Deep Transformer-based Network for Robust and Accurate Local Feature Matching
Tao Xie, Kun Dai, Ke Wang +2
Local feature matching between images remains a challenging task, especially in the presence of significant appearance variations, e.g., extreme viewpoint changes. In this work, we…