no code implementations • 17 Jul 2019 • Chenglong Li, Andong Lu, Aihua Zheng, Zhengzheng Tu, Jin Tang
In a specific, the generality adapter is to extract shared object representations, the modality adapter aims at encoding modality-specific information to deploy their complementary advantages, and the instance adapter is to model the appearance properties and temporal variations of a certain object.
no code implementations • 7 Aug 2019 • Zhengzheng Tu, Yan Ma, Chenglong Li, Jin Tang, Bin Luo
To maintain the clear edge structure of salient objects, we propose a novel Edge-guided Non-local FCN (ENFNet) to perform edge guided feature learning for accurate salient object detection.
no code implementations • 17 Mar 2020 • Zhengzheng Tu, Chun Lin, Chenglong Li, Jin Tang, Bin Luo
Classifying the confusing samples in the course of RGBT tracking is a quite challenging problem, which hasn't got satisfied solution.
no code implementations • 3 Aug 2023 • Zhengzheng Tu, Qishun Wang, Hongshun Wang, Kunpeng Wang, Chenglong Li
Recently, many breakthroughs are made in the field of Video Object Detection (VOD), but the performance is still limited due to the imaging limitations of RGB sensors in adverse illumination conditions.
no code implementations • 28 Nov 2023 • Kunpeng Wang, Chenglong Li, Zhengzheng Tu, Zhengyi Liu, Bin Luo
Existing single-modal and multi-modal salient object detection (SOD) methods focus on designing specific architectures tailored for their respective tasks.
no code implementations • 18 Mar 2024 • Zhengzheng Tu, Zigang Zhu, Yayang Duan, Bo Jiang, Qishun Wang, Chaoxue Zhang
The main challenge for ultrasound video-based breast lesion segmentation is how to exploit the lesion cues of both intra-frame and inter-frame simultaneously.
no code implementations • 23 Apr 2024 • Zhengzheng Tu, Le Gu, Xixi Wang, Bo Jiang
To address these issues, in this paper, we develop a novel Breast Ultrasound SAM Adapter, termed Breast Ultrasound Segment Anything Model (BUSSAM), which migrates the SAM to the field of breast ultrasound image segmentation by using the adapter technique.
1 code implementation • 16 May 2019 • Zhengzheng Tu, Tian Xia, Chenglong Li, Xiaoxiao Wang, Yan Ma, Jin Tang
In this paper, we propose an effective approach for RGB-T image saliency detection.
1 code implementation • 9 Aug 2021 • Zhengyi Liu, YuAn Wang, Zhengzheng Tu, Yun Xiao, Bin Tang
In view of the more contribution of high-level features for the performance, we propose a triplet transformer embedding module to enhance them by learning long-range dependencies across layers.
2 code implementations • 5 May 2020 • Zhengzheng Tu, Zhun Li, Chenglong Li, Yang Lang, Jin Tang
Then, we design a novel dual-decoder to conduct the interactions of multi-level features, two modalities and global contexts.
1 code implementation • 15 Dec 2023 • Yuhao Wang, Xuehu Liu, Pingping Zhang, Hu Lu, Zhengzheng Tu, Huchuan Lu
In addition, most of current Transformer-based ReID methods only utilize the global feature of class tokens to achieve the holistic retrieval, ignoring the local discriminative ones.
1 code implementation • 15 Mar 2024 • Pingping Zhang, Yuhao Wang, Yang Liu, Zhengzheng Tu, Huchuan Lu
To address above issues, we propose a novel learning framework named \textbf{EDITOR} to select diverse tokens from vision Transformers for multi-modal object ReID.
2 code implementations • 7 Jul 2020 • Zhengzheng Tu, Yan Ma, Zhun Li, Chenglong Li, Jieming Xu, Yongtao Liu
Salient object detection in complex scenes and environments is a challenging research topic.
2 code implementations • 5 Jun 2020 • Zhengzheng Tu, Zhun Li, Chenglong Li, Yang Lang, Jin Tang
RGBT salient object detection (SOD) aims to segment the common prominent regions of visible and thermal infrared images.