Large-area depth recovery for RGB-D camera. - Zengqiang Yan; Li Yu 003; Zixiang Xiong (ICIP, 2015)

Texture-free large-area depth recovery for planar surfaces. - Zengqiang Yan; Li Yu 003; Zixiang Xiong (MMSP, 2015)

Describing upper body motions based on the Labanotation for learning-from-observation robots. - Katsushi Ikeuchi; Zengqiang Yan; Zhaoyuan Ma; Yoshihiro Sato; Minako Nakamura; Shunsuke Kudoh (CoRR, 2016)

Texture edge-guided depth recovery for structured light-based depth sensor. - Huiping Deng; Jin Wu; Lei Zhu; Zengqiang Yan; Li Yu 003 (Multim. Tools Appl., 2017)

Frequency Estimation of the Plenoptic Function Using the Autocorrelation Theorem. - Changjian Zhu; Li Yu 003; Zengqiang Yan; Sen Xiang (IEEE Trans. Computational Imaging, 2017)

A Deep Model with Shape-Preserving Loss for Gland Instance Segmentation. - Zengqiang Yan; Xin Yang 008; Kwang-Ting (Tim) Cheng (MICCAI (2), 2018)

Describing Upper-Body Motions Based on Labanotation for Learning-from-Observation Robots. - Katsushi Ikeuchi; Zhaoyuan Ma; Zengqiang Yan; Shunsuke Kudoh; Minako Nakamura (Int. J. Comput. Vis., 2018)

Joint Segment-Level and Pixel-Wise Losses for Deep Learning Based Retinal Vessel Segmentation. - Zengqiang Yan; Xin Yang 008; Kwang-Ting Cheng (IEEE Trans. Biomed. Eng., 2018)

A Skeletal Similarity Metric for Quality Evaluation of Retinal Vessel Segmentation. - Zengqiang Yan; Xin Yang 008; Kwang-Ting Cheng (IEEE Trans. Medical Imaging, 2018)

A Three-Stage Deep Learning Model for Accurate Retinal Vessel Segmentation. - Zengqiang Yan; Xin Yang 008; Kwang-Ting Cheng (IEEE J. Biomed. Health Informatics, 2019)

Enabling a Single Deep Learning Model for Accurate Gland Instance Segmentation: A Shape-Aware Adversarial Learning Framework. - Zengqiang Yan; Xin Yang 008; Kwang-Ting Cheng (IEEE Trans. Medical Imaging, 2020)

Exploring intermediate representation for monocular vehicle pose estimation. - Shichao Li 002; Zengqiang Yan; Hongyang Li; Kwang-Ting Cheng (CVPR, 2021)

Variation-Aware Federated Learning With Multi-Source Decentralized Medical Image Data. - Zengqiang Yan; Jeffry Wicaksana; Zhiwei Wang 002; Xin Yang 008; Kwang-Ting Cheng (IEEE J. Biomed. Health Informatics, 2021)

FedRare: Federated Learning with Intra- and Inter-Client Contrast for Effective Rare Disease Classification. - Nannan Wu; Li Yu 003; Xin Yang 008; Kwang-Ting Cheng; Zengqiang Yan (CoRR, 2022)

C2FTrans: Coarse-to-Fine Transformers for Medical Image Segmentation. - Xian Lin; Zengqiang Yan; Li Yu 003; Kwang-Ting Cheng (CoRR, 2022)

Symmetry-Aware Deep Learning for Cerebral Ventricle Segmentation With Intra-Ventricular Hemorrhage. - Yineng Hua; Zengqiang Yan; Zhuo Kuang; Hang Zhang; Xianbo Deng; Li Yu 003 (IEEE J. Biomed. Health Informatics, 2022)

Uncertainty-Aware Deep Learning With Cross-Task Supervision for PHE Segmentation on CT Images. - Zhuo Kuang; Zengqiang Yan; Li Yu 003; Xianbo Deng; Yineng Hua; Shuyun Li (IEEE J. Biomed. Health Informatics, 2022)

Customized Federated Learning for Multi-Source Decentralized Medical Image Classification. - Jeffry Wicaksana; Zengqiang Yan; Xin Yang 008; Yang Liu 165; Lixin Fan; Kwang-Ting Cheng (IEEE J. Biomed. Health Informatics, 2022)

FedNoRo: Towards Noise-Robust Federated Learning by Addressing Class Imbalance and Label Noise Heterogeneity. - Nannan Wu; Li Yu 003; Xuefeng Jiang; Kwang-Ting Cheng; Zengqiang Yan (IJCAI, 2023)

ConvFormer: Plug-and-Play CNN-Style Transformers for Improving Medical Image Segmentation. - Xian Lin; Zengqiang Yan; Xianbo Deng; Chuansheng Zheng; Li Yu 003 (MICCAI (4), 2023)

FedIIC: Towards Robust Federated Learning for Class-Imbalanced Medical Image Classification. - Nannan Wu; Li Yu 003; Xin Yang 008; Kwang-Ting Cheng; Zengqiang Yan (MICCAI (2), 2023)

FCA: Taming Long-tailed Federated Medical Image Classification by Classifier Anchoring. - Jeffry Wicaksana; Zengqiang Yan; Kwang-Ting Cheng (CoRR, 2023)

SAMUS: Adapting Segment Anything Model for Clinically-Friendly and Generalizable Ultrasound Image Segmentation. - Xian Lin; Yangyang Xiang; Li Zhang; Xin Yang 008; Zengqiang Yan; Li Yu 003 (CoRR, 2023)

The Lighter the Better: Rethinking Transformers in Medical Image Segmentation Through Adaptive Pruning. - Xian Lin; Li Yu 003; Kwang-Ting Cheng; Zengqiang Yan (IEEE Trans. Medical Imaging, 2023)

FedMix: Mixed Supervised Federated Learning for Medical Image Segmentation. - Jeffry Wicaksana; Zengqiang Yan; Dong Zhang; Xijie Huang; Huimin Wu 001; Xin Yang 008; Kwang-Ting Cheng (IEEE Trans. Medical Imaging, 2023)

Hierarchical Associative Encoding and Decoding for Bottom-Up Human Pose Estimation. - Congju Du; Zengqiang Yan; Han Yu; Li Yu 003; Zixiang Xiong (IEEE Trans. Circuits Syst. Video Technol., 2023)

BATFormer: Towards Boundary-Aware Lightweight Transformer for Efficient Medical Image Segmentation. - Xian Lin; Li Yu 003; Kwang-Ting Cheng; Zengqiang Yan (IEEE J. Biomed. Health Informatics, 2023)

MMA-Net: Multi-view mixed attention mechanism for facial action unit detection. - Ziqiao Shang; Congju Du; Bingyin Li; Zengqiang Yan; Li Yu 003 (Pattern Recognit. Lett., 2023)

Affinity Feature Strengthening for Accurate, Complete and Robust Vessel Segmentation. - Tianyi Shi; Xiaohuan Ding; Wei Zhou; Feng Pan; Zengqiang Yan; Xiang Bai; Xin Yang 008 (IEEE J. Biomed. Health Informatics, 2023)

Cluster-Re-Supervision: Bridging the Gap Between Image-Level and Pixel-Wise Labels for Weakly Supervised Medical Image Segmentation. - Zhuo Kuang; Zengqiang Yan; Huiyu Zhou 001; Li Yu 003 (IEEE J. Biomed. Health Informatics, 2023)

DTMFormer: Dynamic Token Merging for Boosting Transformer-Based Medical Image Segmentation. - Zhehao Wang; Xian Lin; Nannan Wu; Li Yu 003; Kwang-Ting Cheng; Zengqiang Yan (AAAI, 2024)

FedA3I: Annotation Quality-Aware Aggregation for Federated Medical Image Segmentation against Heterogeneous Annotation Noise. - Nannan Wu; Zhaobin Sun; Zengqiang Yan; Li Yu 003 (AAAI, 2024)

From Optimization to Generalization: Fair Federated Learning against Quality Shift via Inter-Client Sharpness Matching. - Nannan Wu; Zhuo Kuang; Zengqiang Yan; Li Yu 003 (IJCAI, 2024)

Segment Any Cancer in CT Scans Through Equipping SAM with Cross-Slice Interaction and Indicator Prompt. - Xian Lin; Zhehao Wang; Caozhi Shang; Junjie Shi; Zengqiang Yan; Li Yu 003 (FLARE@MICCAI, 2024)

Revisiting Self-attention in Medical Transformers via Dependency Sparsification. - Xian Lin; Zhehao Wang; Zengqiang Yan; Li Yu 003 (MICCAI (11), 2024)

Beyond Adapting SAM: Towards End-to-End Ultrasound Image Segmentation via Auto Prompting. - Xian Lin; Yangyang Xiang; Li Yu 003; Zengqiang Yan (MICCAI (8), 2024)

FedMLP: Federated Multi-label Medical Image Classification Under Task Heterogeneity. - Zhaobin Sun; Nannan Wu; Junjie Shi; Li Yu 003; Kwang-Ting Cheng; Zengqiang Yan (MICCAI (10), 2024)

CDL-UNet: Curriculum-Driven Lightweight 3D U-Net for Abdominal Organ Segmentation. - Zhehao Wang; Xian Lin; Junjie Shi; Caozhi Shang; Li Yu 003; Zengqiang Yan (FLARE@MICCAI, 2024)

FedIA: Federated Medical Image Segmentation with Heterogeneous Annotation Completeness. - Yangyang Xiang; Nannan Wu; Li Yu 003; Xin Yang 008; Kwang-Ting Cheng; Zengqiang Yan (MICCAI (10), 2024)

PASSION: Towards Effective Incomplete Multi-Modal Medical Image Segmentation with Imbalanced Missing Rates. - Junjie Shi; Caozhi Shang; Zhaobin Sun; Li Yu 003; Xin Yang 008; Zengqiang Yan (ACM Multimedia, 2024)

SAMPE: Auto-Prompting SAM for Generalizable Power Equipment Image Segmentation. - Yuanshan Guo; Rui Gong; Dong Li; Yangyang Wu; Xiaojing Zhao; Yue Liu; Zengqiang Yan (IEEE Access, 2024)

Weakly supervised learning for multi-class medical image segmentation via feature decomposition. - Zhuo Kuang; Zengqiang Yan; Li Yu 003 (Comput. Biol. Medicine, 2024)

FedMLP: Federated Multi-Label Medical Image Classification under Task Heterogeneity. - Zhaobin Sun; Nannan Wu; Junjie Shi; Li Yu 003; Xin Yang 008; Kwang-Ting Cheng; Zengqiang Yan (CoRR, 2024)

Non-parametric regularization for class imbalance federated medical image classification. - Jeffry Wicaksana; Zengqiang Yan; Kwang-Ting Cheng (CoRR, 2024)

Boosting integral-based human pose estimation through implicit heatmap learning. - Congju Du; Zengqiang Yan; Zixiang Xiong; Li Yu 003 (Neural Networks, 2024)

UCTNet: Uncertainty-guided CNN-Transformer hybrid networks for medical image segmentation. - Xiayu Guo; Xian Lin; Xin Yang 008; Li Yu 003; Kwang-Ting Cheng; Zengqiang Yan (Pattern Recognit., 2024)

APCAFlow: All-Pairs Cost Volume Aggregation for Optical Flow Estimation. - Miaojie Feng; Hao Jia; Zengqiang Yan; Xin Yang 008 (IEEE Trans. Multim., 2024)

MFTrans: Modality-Masked Fusion Transformer for Incomplete Multi-Modality Brain Tumor Segmentation. - Junjie Shi; Li Yu 003; Qimin Cheng; Xin Yang 008; Kwang-Ting Cheng; Zengqiang Yan (IEEE J. Biomed. Health Informatics, 2024)

FedIOD: Federated Multi-Organ Segmentation From Partial Labels by Exploring Inter-Organ Dependency. - Qin Wan 002; Zengqiang Yan; Li Yu 003 (IEEE J. Biomed. Health Informatics, 2024)

Fair Federated Medical Image Classification Against Quality Shift via Inter-Client Progressive State Matching. - Nannan Wu; Zhuo Kuang; Zengqiang Yan; Ping Wang; Li Yu 003 (CoRR, 2025)

FedPCA: Noise-Robust Fair Federated Learning via Performance-Capacity Analysis. - Nannan Wu; Zengqiang Yan; Nong Sang; Li Yu 003; Chang Wen Chen (CoRR, 2025)

SAMCT: Segment Any CT Allowing Labor-Free Task-Indicator Prompts. - Xian Lin; Yangyang Xiang; Zhehao Wang; Kwang-Ting Cheng; Zengqiang Yan; Li Yu 003 (IEEE Trans. Medical Imaging, 2025)

ROXSI: Robust Cross-Sequence Semantic Interaction for Brain Tumor Segmentation on Multi-Sequence MR Images. - Zhuo Kuang; Zengqiang Yan; Aly Abayazeed; Franca Wagner; Li Yu 003; Mauricio Reyes 001 (IEEE J. Biomed. Health Informatics, 2025)