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Yiguang Liu

4 accepted papers

2024

A Point-Line Features Fusion Method for Fast and Robust Monocular Visual-Inertial Initialization

IROS 2024poster

Fast and robust initialization is essential for highly accurate monocular visual-inertial odometer (VIO), but at present majority of initialization methods rely only on point features, unstable in low texture and blurring situations. Therefore, we propose a novel point-line features fusion method fo…

Cited by 0SourceScholar
2024

Multi-Modality Speech Recognition Driven by Background Visual Scenes

ICASSP 2024accepted

Visual information is often used as a complementary cue for automatic speech recognition in noisy environments. Most previous studies utilize visual information of target speakers (e.g., lip movements) to improve the recognition performance of audio-visual speech recognition (AVSR) models. However,…

Cited by 0SourceScholar
2021

Gaussian Fusion: Accurate 3D Reconstruction via Geometry-Guided Displacement Interpolation

ICCV 2021poster

Reconstructing delicate geometric details with consumer RGB-D sensors is challenging due to sensor depth and poses uncertainties. To tackle this problem, we propose a unique geometry-guided fusion framework: 1) First, we characterize fusion correspondences with the geodesic curves derived from the m…

Cited by 6PDFScholar
2020

MARMVS: Matching Ambiguity Reduced Multiple View Stereo for Efficient Large Scale Scene Reconstruction

CVPR 2020poster

The ambiguity in image matching is one of main factors decreasing the quality of the 3D model reconstructed by PatchMatch based multiple view stereo. In this paper, we present a novel method, matching ambiguity reduced multiple view stereo (MARMVS) to address this issue. The MARMVS handles the ambig…

Cited by 55PDFScholar