most citedWeakly-Supervised Online Action Segmentation in Multi-View Instructional Videos

1 citations · 1 across the 2 of their papers we have counts for

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6 papers

cs.CV20221 cited

Weakly-Supervised Online Action Segmentation in Multi-View Instructional Videos

Reza Ghoddoosian, Isht Dwivedi, Nakul Agarwal +2

This paper addresses a new problem of weakly-supervised online action segmentation in instructional videos. We present a framework to segment streaming videos online at test time u…

cs.CV2020

Social-STAGE: Spatio-Temporal Multi-Modal Future Trajectory Forecast

Srikanth Malla, Chiho Choi, Behzad Dariush

This paper considers the problem of multi-modal future trajectory forecast with ranking. Here, multi-modality and ranking refer to the multiple plausible path predictions and the c…

cs.CV2020

Unsupervised Domain Adaptation for Spatio-Temporal Action Localization

Nakul Agarwal, Yi-Ting Chen, Behzad Dariush +1

Spatio-temporal action localization is an important problem in computer vision that involves detecting where and when activities occur, and therefore requires modeling of both spat…

cs.CV2020

Recognition and 3D Localization of Pedestrian Actions from Monocular Video

Jun Hayakawa, Behzad Dariush

Understanding and predicting pedestrian behavior is an important and challenging area of research for realizing safe and effective navigation strategies in automated and advanced d…

cs.CV2020

Ego-motion and Surrounding Vehicle State Estimation Using a Monocular Camera

Jun Hayakawa, Behzad Dariush

Understanding ego-motion and surrounding vehicle state is essential to enable automated driving and advanced driving assistance technologies. Typical approaches to solve this probl…

cs.CV2020

SSP: Single Shot Future Trajectory Prediction

Isht Dwivedi, Srikanth Malla, Behzad Dariush +1

We propose a robust solution to future trajectory forecast, which can be practically applicable to autonomous agents in highly crowded environments. For this, three aspects are par…