Search Results for author: Zelun Luo

Found 11 papers, 3 papers with code

Differentially Private Video Activity Recognition

no code implementations27 Jun 2023 Zelun Luo, Yuliang Zou, Yijin Yang, Zane Durante, De-An Huang, Zhiding Yu, Chaowei Xiao, Li Fei-Fei, Animashree Anandkumar

In recent years, differential privacy has seen significant advancements in image classification; however, its application to video activity recognition remains under-explored.

Activity Recognition Classification +2

MOMA: Multi-Object Multi-Actor Activity Parsing

no code implementations NeurIPS 2021 Zelun Luo, Wanze Xie, Siddharth Kapoor, Yiyun Liang, Michael Cooper, Juan Carlos Niebles, Ehsan Adeli, Fei-Fei Li

This paper introduces Activity Parsing as the overarching task of temporal segmentation and classification of activities, sub-activities, atomic actions, along with an instance-level understanding of actors, objects, and their relationships in videos.

Object

Scalable Differential Privacy With Sparse Network Finetuning

no code implementations CVPR 2021 Zelun Luo, Daniel J. Wu, Ehsan Adeli, Li Fei-Fei

We propose a novel method for privacy-preserving training of deep neural networks leveraging public, out-domain data.

Privacy Preserving Transfer Learning

Vision-Based Gait Analysis for Senior Care

no code implementations1 Dec 2018 David Xue, Anin Sayana, Evan Darke, Kelly Shen, Jun-Ting Hsieh, Zelun Luo, Li-Jia Li, N. Lance Downing, Arnold Milstein, Li Fei-Fei

As the senior population rapidly increases, it is challenging yet crucial to provide effective long-term care for seniors who live at home or in senior care facilities.

DF-Net: Unsupervised Joint Learning of Depth and Flow using Cross-Task Consistency

1 code implementation ECCV 2018 Yuliang Zou, Zelun Luo, Jia-Bin Huang

We present an unsupervised learning framework for simultaneously training single-view depth prediction and optical flow estimation models using unlabeled video sequences.

Depth And Camera Motion Depth Prediction +1

Graph Distillation for Action Detection with Privileged Modalities

1 code implementation ECCV 2018 Zelun Luo, Jun-Ting Hsieh, Lu Jiang, Juan Carlos Niebles, Li Fei-Fei

We propose a technique that tackles action detection in multimodal videos under a realistic and challenging condition in which only limited training data and partially observed modalities are available.

Action Classification Action Detection +1

Unsupervised Learning of Long-Term Motion Dynamics for Videos

no code implementations CVPR 2017 Zelun Luo, Boya Peng, De-An Huang, Alexandre Alahi, Li Fei-Fei

We present an unsupervised representation learning approach that compactly encodes the motion dependencies in videos.

Representation Learning

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