Search Results for author: Yonghan Lee

Found 8 papers, 0 papers with code

Array Configuration-Agnostic Personalized Speech Enhancement using Long-Short-Term Spatial Coherence

no code implementations16 Nov 2022 Yicheng Hsu, Yonghan Lee, Mingsian R. Bai

Personalized speech enhancement has been a field of active research for suppression of speechlike interferers such as competing speakers or TV dialogues.

Speech Enhancement

Multi-channel target speech enhancement based on ERB-scaled spatial coherence features

no code implementations17 Jul 2022 Yicheng Hsu, Yonghan Lee, Mingsian R. Bai

Recently, speech enhancement technologies that are based on deep learning have received considerable research attention.

Speech Enhancement

A Single Correspondence Is Enough: Robust Global Registration to Avoid Degeneracy in Urban Environments

no code implementations13 Mar 2022 Hyungtae Lim, Suyong Yeon, Soohyun Ryu, Yonghan Lee, Youngji Kim, JaeSeong Yun, Euigon Jung, Donghwan Lee, Hyun Myung

As verified in indoor and outdoor 3D LiDAR datasets, our proposed method yields robust global registration performance compared with other global registration methods, even for distant point cloud pairs.

SelfTune: Metrically Scaled Monocular Depth Estimation through Self-Supervised Learning

no code implementations10 Mar 2022 Jaehoon Choi, Dongki Jung, Yonghan Lee, Deokhwa Kim, Dinesh Manocha, Donghwan Lee

Given these metric poses and monocular sequences, we propose a self-supervised learning method for the pre-trained supervised monocular depth networks to enable metrically scaled depth estimation.

Monocular Depth Estimation Robot Navigation +2

Learning-based personal speech enhancement for teleconferencing by exploiting spatial-spectral features

no code implementations10 Dec 2021 Yicheng Hsu, Yonghan Lee, Mingsian R. Bai

Furthermore, the proposed enhancement system was compared with a baseline system with speaker embeddings and interchannel phase difference.

Speech Enhancement Speech Extraction

DnD: Dense Depth Estimation in Crowded Dynamic Indoor Scenes

no code implementations ICCV 2021 Dongki Jung, Jaehoon Choi, Yonghan Lee, Deokhwa Kim, Changick Kim, Dinesh Manocha, Donghwan Lee

We present a novel approach for estimating depth from a monocular camera as it moves through complex and crowded indoor environments, e. g., a department store or a metro station.

3D Reconstruction Depth Estimation

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