38 citations · 72 across the 9 of their papers we have counts for
22 papers
Forecasting Human Trajectory from Scene History
Mancheng Meng, Ziyan Wu, Terrence Chen +4
Predicting the future trajectory of a person remains a challenging problem, due to randomness and subjectivity of human movement. However, the moving patterns of human in a constra…
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…
Self-supervised Human Mesh Recovery with Cross-Representation Alignment
Xuan Gong, Meng Zheng, Benjamin Planche +4
Fully supervised human mesh recovery methods are data-hungry and have poor generalizability due to the limited availability and diversity of 3D-annotated benchmark datasets. Recent…
Spatio-Temporal Representation Factorization for Video-based Person Re-Identification
Abhishek Aich, Meng Zheng, Srikrishna Karanam +3
Despite much recent progress in video-based person re-identification (re-ID), the current state-of-the-art still suffers from common real-world challenges such as appearance simila…
Learning Local Recurrent Models for Human Mesh Recovery
Runze Li, Srikrishna Karanam, Ren Li +3
We consider the problem of estimating frame-level full human body meshes given a video of a person with natural motion dynamics. While much progress in this field has been in singl…