no code implementations • 22 Feb 2024 • Jun Wang, Yuzhe Qin, Kaiming Kuang, Yigit Korkmaz, Akhilan Gurumoorthy, Hao Su, Xiaolong Wang
We introduce CyberDemo, a novel approach to robotic imitation learning that leverages simulated human demonstrations for real-world tasks.
no code implementations • 14 Feb 2024 • Jiancheng Yang, Rui Shi, Liang Jin, Xiaoyang Huang, Kaiming Kuang, Donglai Wei, Shixuan Gu, Jianying Liu, PengFei Liu, Zhizhong Chai, Yongjie Xiao, Hao Chen, Liming Xu, Bang Du, Xiangyi Yan, Hao Tang, Adam Alessio, Gregory Holste, Jiapeng Zhang, Xiaoming Wang, Jianye He, Lixuan Che, Hanspeter Pfister, Ming Li, Bingbing Ni
The resulting FracNet+ demonstrates competitive performance in rib fracture detection, which lays a foundation for further research and development in AI-assisted rib fracture detection and diagnosis.
1 code implementation • NeurIPS 2023 • Minghua Liu, Ruoxi Shi, Kaiming Kuang, Yinhao Zhu, Xuanlin Li, Shizhong Han, Hong Cai, Fatih Porikli, Hao Su
Due to their alignment with CLIP embeddings, our learned shape representations can also be integrated with off-the-shelf CLIP-based models for various applications, such as point cloud captioning and point cloud-conditioned image generation.
Ranked #5 on Zero-Shot Transfer 3D Point Cloud Classification on ModelNet40 (using extra training data)
1 code implementation • 7 Mar 2023 • Rui Xu, Zhi Liu, Yong Luo, Han Hu, Li Shen, Bo Du, Kaiming Kuang, Jiancheng Yang
To address this issue, we propose a slice grouped domain attention (SGDA) module to enhance the generalization capability of the pulmonary nodule detection networks.
1 code implementation • 18 Oct 2022 • Liang Jin, Shixuan Gu, Donglai Wei, Jason Ken Adhinarta, Kaiming Kuang, Yongjie Jessica Zhang, Hanspeter Pfister, Bingbing Ni, Jiancheng Yang, Ming Li
Based on the RibSeg v2, we develop a pipeline including deep learning-based methods for rib labeling, and a skeletonization-based method for centerline extraction.
1 code implementation • 3 Aug 2022 • Rui Xu, Yong Luo, Bo Du, Kaiming Kuang, Jiancheng Yang
Convolutional neural networks (CNNs) have been demonstrated to be highly effective in the field of pulmonary nodule detection.
1 code implementation • 7 Jul 2022 • Kaiming Kuang, Li Zhang, Jingyu Li, Hongwei Li, Jiajun Chen, Bo Du, Jiancheng Yang
The automatic reconstruction of pulmonary segments by ImPulSe is accurate in metrics and visually appealing.
1 code implementation • 17 Sep 2021 • Jiancheng Yang, Yi He, Kaiming Kuang, Zudi Lin, Hanspeter Pfister, Bingbing Ni
The proposed A3D consistently outperforms symmetric context fusion operators by considerable margins, and establishes a new \emph{state of the art} on DeepLesion.
no code implementations • 8 Oct 2020 • Jiancheng Yang, Mingze Gao, Kaiming Kuang, Bingbing Ni, Yunlang She, Dong Xie, Chang Chen
A three-level hierarchical classification system for pulmonary lesions is developed, which covers most diseases in cancer-related diagnosis.
1 code implementation • 8 Oct 2020 • Jiancheng Yang, Jiajun Chen, Kaiming Kuang, Tiancheng Lin, Junjun He, Bingbing Ni
Furthermore, we experiment the proposed method on an in-house, retrospective dataset of real-world non-small cell lung cancer patients under anti-PD-1 immunotherapy.
Ranked #1 on Text-To-Speech Synthesis on 20000 utterances (using extra training data)