1 code implementation • CVPR 2021 • Zhenguang Liu, Haoming Chen, Runyang Feng, Shuang Wu, Shouling Ji, Bailin Yang, Xun Wang
Multi-frame human pose estimation in complicated situations is challenging.
Ranked #1 on Multi-Person Pose Estimation on PoseTrack2017 (using extra training data)
no code implementations • 20 Oct 2021 • Xin Zhang, Liangxiu Han, Tam Sobeih, Lianghao Han, Nina Dempsey, Symeon Lechareas, Ascanio Tridente, Haoming Chen, Stephen White
The proposed method can provide more detailed high resolution visual explanation for the classification decision, compared to current state-of-the-art visual explanation methods and has a great potential to be used in clinical practice for COVID-19 pneumonia diagnosis.
1 code implementation • CVPR 2022 • Zhenguang Liu, Runyang Feng, Haoming Chen, Shuang Wu, Yixing Gao, Yunjun Gao, Xiang Wang
State-of-the-art methods strive to incorporate additional visual evidences from neighboring frames (supporting frames) to facilitate the pose estimation of the current frame (key frame).
no code implementations • 15 Apr 2022 • Haoming Chen, Runyang Feng, Sifan Wu, Hao Xu, Fengcheng Zhou, Zhenguang Liu
Briefly, existing approaches put their efforts in three directions, namely network architecture design, network training refinement, and post processing.
no code implementations • 22 Jul 2022 • Samson B. Akintoye, Liangxiu Han, Huw Lloyd, Xin Zhang, Darren Dancey, Haoming Chen, Daoqiang Zhang
Deep Neural Network (DNN) models are usually trained sequentially from one layer to another, which causes forward, backward and update locking's problems, leading to poor performance in terms of training time.
no code implementations • 17 Feb 2023 • Xin Zhang, Liangxiu Han, Lianghao Han, Haoming Chen, Darren Dancey, Daoqiang Zhang
Specifically, it consists of two primary components: 1) A fast and efficient explainable patch selection mechanism for determining the most discriminative patches based on computing the SHapley Additive exPlanations (SHAP) contribution to a transfer learning model for AD diagnosis on massive medical data; and 2) A novel patch-based network for extracting deep features and AD classfication from the selected patches with position embeddings to retain position information, capable of capturing the global and local information of inter- and intra-patches.
1 code implementation • 20 Jul 2023 • Rongsheng Wang, Yaofei Duan, ChanTong Lam, Jiexi Chen, Jiangsheng Xu, Haoming Chen, Xiaohong Liu, Patrick Cheong-Iao Pang, Tao Tan
General large language models (LLMs) such as ChatGPT have shown remarkable success.
no code implementations • 28 Nov 2023 • Hao Pei, Si Lin, Chuanfu Li, Che Wang, Haoming Chen, Sizhe Li
To enhance the intelligence degree in operation and maintenance, a novel method for fault detection in power grids is proposed.
1 code implementation • 22 Dec 2023 • Rongsheng Wang, Haoming Chen, Ruizhe Zhou, Yaofei Duan, Kunyan Cai, Han Ma, Jiaxi Cui, Jian Li, Patrick Cheong-Iao Pang, Yapeng Wang, Tao Tan
This work is pioneering in the execution of instruction fine-tuning on a sparse expert-mixed model, marking a significant breakthrough in enhancing the capabilities of this model architecture.
1 code implementation • 2 Feb 2024 • Rongsheng Wang, Haoming Chen, Ruizhe Zhou, Han Ma, Yaofei Duan, Yanlan Kang, Songhua Yang, Baoyu Fan, Tao Tan
We then proposed LLM-Detector, a novel method for both document-level and sentence-level text detection through Instruction Tuning of LLMs.