activity
20152022
most citedNear-Online Multi-target Tracking with Aggregated Local Flow Descriptor

24 citations · 35 across the 3 of their papers we have counts for

collaborators

6 papers

cs.CV20223 cited

3SD: Self-Supervised Saliency Detection With No Labels

Rajeev Yasarla, Renliang Weng, Wongun Choi +2

We present a conceptually simple self-supervised method for saliency detection. Our method generates and uses pseudo-ground truth labels for training. The generated pseudo-GT label…

cs.CV20218 cited

Learning a Proposal Classifier for Multiple Object Tracking

Peng Dai, Renliang Weng, Wongun Choi +3

The recent trend in multiple object tracking (MOT) is heading towards leveraging deep learning to boost the tracking performance. However, it is not trivial to solve the data-assoc…

cs.CV2019

Multi-Agent Tensor Fusion for Contextual Trajectory Prediction

Tianyang Zhao, Yifei Xu, Mathew Monfort +5

Accurate prediction of others' trajectories is essential for autonomous driving. Trajectory prediction is challenging because it requires reasoning about agents' past movements, so…

cs.CV2018

Memory Warps for Learning Long-Term Online Video Representations

Tuan-Hung Vu, Wongun Choi, Samuel Schulter +1

This paper proposes a novel memory-based online video representation that is efficient, accurate and predictive. This is in contrast to prior works that often rely on computational…

cs.CV2017

Deep Network Flow for Multi-Object Tracking

Samuel Schulter, Paul Vernaza, Wongun Choi +1

Data association problems are an important component of many computer vision applications, with multi-object tracking being one of the most prominent examples. A typical approach t…

cs.CV201524 cited

Near-Online Multi-target Tracking with Aggregated Local Flow Descriptor

Wongun Choi

In this paper, we focus on the two key aspects of multiple target tracking problem: 1) designing an accurate affinity measure to associate detections and 2) implementing an efficie…