Search Results for author: Ruifeng Li

Found 11 papers, 7 papers with code

OFVL-MS: Once for Visual Localization across Multiple Indoor Scenes

1 code implementation ICCV 2023 Tao Xie, Kun Dai, Siyi Lu, Ke Wang, Zhiqiang Jiang, Jinghan Gao, Dedong Liu, Jie Xu, Lijun Zhao, Ruifeng Li

In this work, we seek to predict camera poses across scenes with a multi-task learning manner, where we view the localization of each scene as a new task.

Multi-Task Learning Visual Localization

Multiscale Positive-Unlabeled Detection of AI-Generated Texts

3 code implementations29 May 2023 Yuchuan Tian, Hanting Chen, Xutao Wang, Zheyuan Bai, Qinghua Zhang, Ruifeng Li, Chao Xu, Yunhe Wang

Recent releases of Large Language Models (LLMs), e. g. ChatGPT, are astonishing at generating human-like texts, but they may impact the authenticity of texts.

Language Modelling text-classification +2

Pillar R-CNN for Point Cloud 3D Object Detection

1 code implementation26 Feb 2023 Guangsheng Shi, Ruifeng Li, Chao Ma

The performance of point cloud 3D object detection hinges on effectively representing raw points, grid-based voxels or pillars.

3D Object Detection Autonomous Driving +1

An Electromagnetic-Information-Theory Based Model for Efficient Characterization of MIMO Systems in Complex Space

no code implementations13 Jan 2023 Ruifeng Li, Da Li, Jinyan Ma, Zhaoyang Feng, Ling Zhang, Shurun Tan, Wei E. I. Sha, Hongsheng Chen, Er-Ping Li

In this manuscript, an Electromagnetic-Information-Theory (EMIT) based model is developed for efficient characterization of MIMO systems in complex space.

DeepMatcher: A Deep Transformer-based Network for Robust and Accurate Local Feature Matching

1 code implementation8 Jan 2023 Tao Xie, Kun Dai, Ke Wang, Ruifeng Li, Lijun Zhao

In this work, we propose DeepMatcher, a deep Transformer-based network built upon our investigation of local feature matching in detector-free methods.

Poly-PC: A Polyhedral Network for Multiple Point Cloud Tasks at Once

no code implementations CVPR 2023 Tao Xie, Shiguang Wang, Ke Wang, Linqi Yang, Zhiqiang Jiang, Xingcheng Zhang, Kun Dai, Ruifeng Li, Jian Cheng

In this work, we show that it is feasible to perform multiple tasks concurrently on point cloud with a straightforward yet effective multi-task network.

Incremental Learning Multi-Task Learning

CO-Net: Learning Multiple Point Cloud Tasks at Once with A Cohesive Network

no code implementations ICCV 2023 Tao Xie, Ke Wang, Siyi Lu, Yukun Zhang, Kun Dai, Xiaoyu Li, Jie Xu, Li Wang, Lijun Zhao, Xinyu Zhang, Ruifeng Li

Finally, we propose a sign-based gradient surgery to promote the training of CO-Net, thereby emphasizing the usage of task-shared parameters and guaranteeing that each task can be thoroughly optimized.

Incremental Learning Multi-Task Learning

RSG-Net: Towards Rich Sematic Relationship Prediction for Intelligent Vehicle in Complex Environments

no code implementations16 Jul 2022 Yafu Tian, Alexander Carballo, Ruifeng Li, Kazuya Takeda

Behavioral and semantic relationships play a vital role on intelligent self-driving vehicles and ADAS systems.

Decision Making

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