Search Results for author: Lulu Tang

Found 5 papers, 3 papers with code

Tokenize Anything via Prompting

1 code implementation14 Dec 2023 Ting Pan, Lulu Tang, Xinlong Wang, Shiguang Shan

The semantic token is responsible for learning the semantic priors in a predefined concept space.

Visual Prompting

PU-EVA: An Edge Vector based Approximation Solution for Flexible-scale Point Cloud Upsampling

no code implementations22 Apr 2022 Luqing Luo, Lulu Tang, Wanyi Zhou, Shizheng Wang, Zhi-Xin Yang

In this work, the flexible upsampling rates are achieved via edge vector based affine combinations, and a novel design of Edge Vector based Approximation for Flexible-scale Point clouds Upsampling (PU-EVA) is proposed.

Surface Reconstruction

PU-EVA: An Edge-Vector Based Approximation Solution for Flexible-Scale Point Cloud Upsampling

1 code implementation ICCV 2021 Luqing Luo, Lulu Tang, Wanyi Zhou, Shizheng Wang, Zhi-Xin Yang

In this work, the arbitrary point clouds upsampling rates are achieved via edge-vector based affine combinations, and a novel design of Edge-Vector based Approximation for Flexible-scale Point clouds Upsampling (PU-EVA) is proposed.

Surface Reconstruction

Improving Semantic Analysis on Point Clouds via Auxiliary Supervision of Local Geometric Priors

no code implementations14 Jan 2020 Lulu Tang, Ke Chen, Chaozheng Wu, Yu Hong, Kui Jia, Zhi-Xin Yang

Existing deep learning algorithms for point cloud analysis mainly concern discovering semantic patterns from global configuration of local geometries in a supervised learning manner.

Cannot find the paper you are looking for? You can Submit a new open access paper.