Search Results for author: Xingkui Zhu

Found 4 papers, 4 papers with code

Dynamic Adapter Meets Prompt Tuning: Parameter-Efficient Transfer Learning for Point Cloud Analysis

1 code implementation3 Mar 2024 Xin Zhou, Dingkang Liang, Wei Xu, Xingkui Zhu, Yihan Xu, Zhikang Zou, Xiang Bai

To achieve this goal, we freeze the parameters of the default pre-trained models and then propose the Dynamic Adapter, which generates a dynamic scale for each token, considering the token significance to the downstream task.

Transfer Learning

PointMamba: A Simple State Space Model for Point Cloud Analysis

1 code implementation16 Feb 2024 Dingkang Liang, Xin Zhou, Xinyu Wang, Xingkui Zhu, Wei Xu, Zhikang Zou, Xiaoqing Ye, Xiang Bai

Recently, state space models (SSM), a new family of deep sequence models, have presented great potential for sequence modeling in NLP tasks.

Turning a CLIP Model into a Scene Text Spotter

1 code implementation21 Aug 2023 Wenwen Yu, Yuliang Liu, Xingkui Zhu, Haoyu Cao, Xing Sun, Xiang Bai

Utilizing only 10% of the supervised data, FastTCM-CR50 improves performance by an average of 26. 5% and 5. 5% for text detection and spotting tasks, respectively.

object-detection Object Detection +3

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