most citedCo-Planar Parametrization for Stereo-SLAM and Visual-Inertial Odometry

32 citations · 40 across the 5 of their papers we have counts for

collaborators

6 papers

cs.CV20211 cited

Semantic Dense Reconstruction with Consistent Scene Segments

Yingcai Wan, Yanyan Li, Yingxuan You +3

In this paper, a method for dense semantic 3D scene reconstruction from an RGB-D sequence is proposed to solve high-level scene understanding tasks. First, each RGB-D pair is consi…

cs.CV20212 cited

SRH-Net: Stacked Recurrent Hourglass Network for Stereo Matching

Hongzhi Du, Yanyan Li, Yanbiao Sun +2

The cost aggregation strategy shows a crucial role in learning-based stereo matching tasks, where 3D convolutional filters obtain state of the art but require intensive computation…

cs.CV2021

ManhattanSLAM: Robust Planar Tracking and Mapping Leveraging Mixture of Manhattan Frames

Raza Yunus, Yanyan Li, Federico Tombari

In this paper, a robust RGB-D SLAM system is proposed to utilize the structural information in indoor scenes, allowing for accurate tracking and efficient dense mapping on a CPU. P…

cs.RO2020

RGB-D SLAM with Structural Regularities

Yanyan Li, Raza Yunus, Nikolas Brasch +2

This work proposes a RGB-D SLAM system specifically designed for structured environments and aimed at improved tracking and mapping accuracy by relying on geometric features that a…

cs.RO202032 cited

Co-Planar Parametrization for Stereo-SLAM and Visual-Inertial Odometry

Xin Li, Yanyan Li, Evin Pınar Örnek +2

This work proposes a novel SLAM framework for stereo and visual inertial odometry estimation. It builds an efficient and robust parametrization of co-planar points and lines which…

cs.RO20205 cited

Structure-SLAM: Low-Drift Monocular SLAM in Indoor Environments

Yanyan Li, Nikolas Brasch, Yida Wang +2

In this paper a low-drift monocular SLAM method is proposed targeting indoor scenarios, where monocular SLAM often fails due to the lack of textured surfaces. Our approach decouple…