6 papers
Neural Finite-State Machines for Surgical Phase Recognition
Hao Ding, Zhongpai Gao, Benjamin Planche +7
Surgical phase recognition (SPR) is crucial for applications in workflow optimization, performance evaluation, and real-time intervention guidance. However, current deep learning m…
Divide and Fuse: Body Part Mesh Recovery from Partially Visible Human Images
Tianyu Luan, Zhongpai Gao, Luyuan Xie +8
We introduce a novel bottom-up approach for human body mesh reconstruction, specifically designed to address the challenges posed by partial visibility and occlusion in input image…
Automated Patient Positioning with Learned 3D Hand Gestures
Zhongpai Gao, Abhishek Sharma, Meng Zheng +3
Positioning patients for scanning and interventional procedures is a critical task that requires high precision and accuracy. The conventional workflow involves manually adjusting…
PBADet: A One-Stage Anchor-Free Approach for Part-Body Association
Zhongpai Gao, Huayi Zhou, Abhishek Sharma +4
The detection of human parts (e.g., hands, face) and their correct association with individuals is an essential task, e.g., for ubiquitous human-machine interfaces and action recog…
Federated Learning with Privacy-Preserving Ensemble Attention Distillation
Xuan Gong, Liangchen Song, Rishi Vedula +8
Federated Learning (FL) is a machine learning paradigm where many local nodes collaboratively train a central model while keeping the training data decentralized. This is particula…
Preserving Privacy in Federated Learning with Ensemble Cross-Domain Knowledge Distillation
Xuan Gong, Abhishek Sharma, Srikrishna Karanam +4
Federated Learning (FL) is a machine learning paradigm where local nodes collaboratively train a central model while the training data remains decentralized. Existing FL methods ty…