no code implementations • 14 Apr 2024 • Diandian Guo, Manxi Lin, Jialun Pei, He Tang, Yueming Jin, Pheng-Ann Heng
A comprehensive understanding of surgical scenes allows for monitoring of the surgical process, reducing the occurrence of accidents and enhancing efficiency for medical professionals.
no code implementations • 22 Feb 2024 • Jialun Pei, Diandian Guo, Jingyang Zhang, Manxi Lin, Yueming Jin, Pheng-Ann Heng
In this study, we introduce a novel single-stage bimodal transformer framework for SGG in the OR, termed S^2Former-OR, aimed to complementally leverage multi-view 2D scenes and 3D point clouds for SGG in an end-to-end manner.
1 code implementation • 14 Aug 2023 • Bo Dong, Jialun Pei, Rongrong Gao, Tian-Zhu Xiang, Shuo Wang, Huan Xiong
Due to the high similarity between camouflaged instances and the background, the recently proposed camouflaged instance segmentation (CIS) faces challenges in accurate localization and instance segmentation.
1 code implementation • 1 Aug 2023 • Chengxiao Sun, Yan Xu, Jialun Pei, Haopeng Fang, He Tang
The ranking by partition paradigm alleviates ranking ambiguities in a general sense, as it consistently improves the performance of other saliency ranking models.
1 code implementation • 26 Jul 2023 • Jialun Pei, Zhangjun Zhou, Yueming Jin, He Tang, Pheng-Ann Heng
First, a dual-size input feeds into the shared backbone to produce more holistic and detailed features while keeping the model lightweight.
1 code implementation • 16 Jul 2023 • Jialun Pei, Tao Jiang, He Tang, Nian Liu, Yueming Jin, Deng-Ping Fan, Pheng-Ann Heng
We propose a novel approach for RGB-D salient instance segmentation using a dual-branch cross-modal feature calibration architecture called CalibNet.
1 code implementation • 5 Jul 2022 • Jialun Pei, Tianyang Cheng, Deng-Ping Fan, He Tang, Chuanbo Chen, Luc van Gool
We present OSFormer, the first one-stage transformer framework for camouflaged instance segmentation (CIS).
no code implementations • 19 Aug 2020 • Jialun Pei, He Tang, Tianyang Cheng, Chuanbo Chen
To this end, we present a cyclic global context salient instance segmentation network (CGCNet), which is supervised by the combination of salient regions and bounding boxes from the ready-made salient object detection datasets.
no code implementations • 29 Sep 2019 • Jialun Pei, He Tang, Chao Liu, Chuanbo Chen
The experimental results on both salient region detection and salient instance segmentation datasets demonstrate the satisfactory performance of our framework.