activity
20182021
most citedManipulation-skill Assessment from Videos with Spatial Attention Network

4 citations · 8 across the 3 of their papers we have counts for

collaborators

5 papers

cs.CV20213 cited

Uncertainty-Aware Model Adaptation for Unsupervised Cross-Domain Object Detection

Minjie Cai, Minyi Luo, Xionghu Zhong +1

This work tackles the unsupervised cross-domain object detection problem which aims to generalize a pre-trained object detector to a new target domain without labels. We propose an…

cs.CV20191 cited

What I See Is What You See: Joint Attention Learning for First and Third Person Video Co-analysis

Huangyue Yu, Minjie Cai, Yunfei Liu +1

In recent years, more and more videos are captured from the first-person viewpoint by wearable cameras. Such first-person video provides additional information besides the traditio…

cs.CV20194 cited

Manipulation-skill Assessment from Videos with Spatial Attention Network

Zhenqiang Li, Yifei Huang, Minjie Cai +1

Recent advances in computer vision have made it possible to automatically assess from videos the manipulation skills of humans in performing a task, which breeds many important app…

cs.CV2018

Understanding hand-object manipulation by modeling the contextual relationship between actions, grasp types and object attributes

Minjie Cai, Kris Kitani, Yoichi Sato

This paper proposes a novel method for understanding daily hand-object manipulation by developing computer vision-based techniques. Specifically, we focus on recognizing hand grasp…

cs.CV2018

Predicting Gaze in Egocentric Video by Learning Task-dependent Attention Transition

Yifei Huang, Minjie Cai, Zhenqiang Li +1

We present a new computational model for gaze prediction in egocentric videos by exploring patterns in temporal shift of gaze fixations (attention transition) that are dependent on…