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Mengyu He

2 accepted papers

2024

DeconfuseTrack: Dealing with Confusion for Multi-Object Tracking

CVPR 2024poster

Accurate data association is crucial in reducing confusion such as ID switches and assignment errors in multi-object tracking (MOT). However existing advanced methods often overlook the diversity among trajectories and the ambiguity and conflicts present in motion and appearance cues leading to conf…

Cited by 5Source ↗PDF ↗Scholar ↗
2021

Improving Multimodal Speech Enhancement by Incorporating Self-Supervised and Curriculum Learning

ICASSP 2021accepted

Speech enhancement in realistic scenarios still remains many challenges, such as complex background signals and data limitations. In this paper, we present a co-attention based framework that incorporates self-supervised and curriculum learning to derive the target speech in noisy environments. Spec…

Cited by 6Source ↗Scholar ↗