no code implementations • 15 Sep 2023 • Fangbo Qin, Taogang Hou, Shan Lin, Kaiyuan Wang, Michael C. Yip, Shan Yu
Towards flexible object-centric visual perception, we propose a one-shot instance-aware object keypoint (OKP) extraction approach, AnyOKP, which leverages the powerful representation ability of pretrained vision transformer (ViT), and can obtain keypoints on multiple object instances of arbitrary category after learning from a support image.
1 code implementation • 15 Apr 2022 • XiaoFeng Wang, Zheng Zhu, Fangbo Qin, Yun Ye, Guan Huang, Xu Chi, Yijia He, Xingang Wang
Therefore, we present MVSTER, which leverages the proposed epipolar Transformer to learn both 2D semantics and 3D spatial associations efficiently.
no code implementations • ICCV 2021 • Haotian Zhang, Yicheng Luo, Fangbo Qin, Yijia He, Xiao Liu
The line description ability of ELSD also outperforms the previous works on the line matching task.
Ranked #1 on
Line Segment Detection
on wireframe dataset
no code implementations • 17 Nov 2020 • Shan Lin, Fangbo Qin, Haonan Peng, Randall A. Bly, Kris S. Moe, Blake Hannaford
However, the high computation cost may limit the application of deep models to time-sensitive tasks such as online surgical video analysis for robotic-assisted surgery.
no code implementations • 7 Oct 2020 • Fangbo Qin, Jie Qin, Siyu Huang, De Xu
For the novel CPI extraction task, we built the Object Contour Primitives dataset using online public images, and the Robotic Object Contour Measurement dataset using a camera mounted on a robot.
2 code implementations • ECCV 2020 • Siyu Huang, Fangbo Qin, Pengfei Xiong, Ning Ding, Yijia He, Xiao Liu
To realize one-step detection with a faster and more compact model, we introduce the tri-points representation, converting the line segment detection to the end-to-end prediction of a root-point and two endpoints for each line segment.
Ranked #2 on
Line Segment Detection
on York Urban Dataset
1 code implementation • 10 Mar 2020 • Shan Lin, Fangbo Qin, Yangming Li, Randall A. Bly, Kris S. Moe, Blake Hannaford
For live image segmentation, we first translate the live images to fake-cadaveric images with LC-GAN and then perform segmentation on the fake-cadaveric images with models trained on the real cadaveric dataset.
1 code implementation • 25 Feb 2020 • Fangbo Qin, Shan Lin, Yangming Li, Randall A. Bly, Kris S. Moe, Blake Hannaford
Accurate and real-time surgical instrument segmentation is important in the endoscopic vision of robot-assisted surgery, and significant challenges are posed by frequent instrument-tissue contacts and continuous change of observation perspective.