Jiyang Gao

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Temporal Action Proposal (TAP) generation is an important problem, as fast and accurate extraction of semantically important (e.g. human actions) segments from untrimmed videos is an important step for large-scale video analysis. We propose a novel Temporal Unit Regression Network (TURN) model. There are two salient aspects of TURN: (1) TURN jointly(More)
To improve the positioning accuracy of implants in Total Hip Replacement (THR) surgeries, a visual-aided wireless monitoring system for THR surgery is proposed in this paper. This system aims to measure and display the contact distribution and relative pose between femoral head and acetabulum prosthesis during the surgery to help surgeons obtain accurate(More)
Temporal action detection in long videos is an important problem. State-of-the-art methods address this problem by applying action classifiers on sliding windows. Although sliding windows may contain an identifiable portion of the actions, they may not necessarily cover the entire action instance, which would lead to inferior performance. We adapt a(More)
This paper focuses on temporal localization of actions in untrimmed videos. Existing methods typically train classifiers for a pre-defined list of actions and apply them in a sliding window fashion. However, activities in the wild consist of a wide combination of actors, actions and objects; it is difficult to design a proper activity list that meets users’(More)
Action classification in still images has been a popular research topic in computer vision. Labelling large scale datasets for action classification requires tremendous manual work, which is hard to scale up. Besides, the action categories in such datasets are pre-defined and vocabularies are fixed. However humans may describe the same action with different(More)
1 Institute of Microelectronics, Tsinghua University, Haidian, Beijing, China Abstract. Numerous factors influence the rate of dislocation after total hip replacement (THR) surgeries and malposition of the acetabular and femoral component has long been recognized as an important cause. To help surgeons improve the accuracy of the positioning of the(More)
In this work, we address the problem of spatio-temporal action detection in temporally untrimmed videos. It is an important and challenging task as finding accurate human actions in both temporal and spatial space is important for analyzing large-scale video data. To tackle this problem, we propose a cascade proposal and location anticipation (CPLA) model(More)