Search Results for author: Zhuoxiao Chen

Found 11 papers, 8 papers with code

DiPEx: Dispersing Prompt Expansion for Class-Agnostic Object Detection

1 code implementation21 Jun 2024 Jia Syuen Lim, Zhuoxiao Chen, Mahsa Baktashmotlagh, Zhi Chen, Xin Yu, Zi Huang, Yadan Luo

We demonstrate the effectiveness of DiPEx through extensive class-agnostic OD and OOD-OD experiments on MS-COCO and LVIS, surpassing other prompting methods by up to 20. 1% in AR and achieving a 21. 3% AP improvement over SAM.

Class-agnostic Object Detection Multi-object discovery +3

MOS: Model Synergy for Test-Time Adaptation on LiDAR-Based 3D Object Detection

no code implementations21 Jun 2024 Zhuoxiao Chen, Junjie Meng, Mahsa Baktashmotlagh, Yonggang Zhang, Zi Huang, Yadan Luo

Specifically, we propose a Model Synergy (MOS) strategy that dynamically selects historical checkpoints with diverse knowledge and assembles them to best accommodate the current test batch.

3D Object Detection object-detection +1

DPO: Dual-Perturbation Optimization for Test-time Adaptation in 3D Object Detection

1 code implementation19 Jun 2024 Zhuoxiao Chen, Zixin Wang, Yadan Luo, Sen Wang, Zi Huang

We minimize the sharpness to cultivate a flat loss landscape to ensure model resiliency to minor data variations, thereby enhancing the generalization of the adaptation process.

3D Object Detection object-detection +1

In Search of Lost Online Test-time Adaptation: A Survey

1 code implementation31 Oct 2023 Zixin Wang, Yadan Luo, Liang Zheng, Zhuoxiao Chen, Sen Wang, Zi Huang

This article presents a comprehensive survey of online test-time adaptation (OTTA), focusing on effectively adapting machine learning models to distributionally different target data upon batch arrival.

Benchmarking Survey +1

Open-CRB: Towards Open World Active Learning for 3D Object Detection

1 code implementation16 Oct 2023 Zhuoxiao Chen, Yadan Luo, Zixin Wang, Zijian Wang, Xin Yu, Zi Huang

This paper investigates a more practical and challenging research task: Open World Active Learning for 3D Object Detection (OWAL-3D), aimed at acquiring informative point clouds with new concepts.

3D Object Detection Active Learning +3

Revisiting Domain-Adaptive 3D Object Detection by Reliable, Diverse and Class-balanced Pseudo-Labeling

1 code implementation ICCV 2023 Zhuoxiao Chen, Yadan Luo, Zheng Wang, Mahsa Baktashmotlagh, Zi Huang

Unsupervised domain adaptation (DA) with the aid of pseudo labeling techniques has emerged as a crucial approach for domain-adaptive 3D object detection.

3D Object Detection object-detection +1

KECOR: Kernel Coding Rate Maximization for Active 3D Object Detection

no code implementations ICCV 2023 Yadan Luo, Zhuoxiao Chen, Zhen Fang, Zheng Zhang, Zi Huang, Mahsa Baktashmotlagh

Achieving a reliable LiDAR-based object detector in autonomous driving is paramount, but its success hinges on obtaining large amounts of precise 3D annotations.

3D Object Detection Active Learning +4

Exploring Active 3D Object Detection from a Generalization Perspective

1 code implementation23 Jan 2023 Yadan Luo, Zhuoxiao Chen, Zijian Wang, Xin Yu, Zi Huang, Mahsa Baktashmotlagh

To alleviate the high annotation cost in LiDAR-based 3D object detection, active learning is a promising solution that learns to select only a small portion of unlabeled data to annotate, without compromising model performance.

3D Object Detection Active Learning +2

Source-Free Progressive Graph Learning for Open-Set Domain Adaptation

2 code implementations13 Feb 2022 Yadan Luo, Zijian Wang, Zhuoxiao Chen, Zi Huang, Mahsa Baktashmotlagh

However, most existing OSDA approaches are limited due to three main reasons, including: (1) the lack of essential theoretical analysis of generalization bound, (2) the reliance on the coexistence of source and target data during adaptation, and (3) failing to accurately estimate the uncertainty of model predictions.

Action Recognition Domain Adaptation +2

RoadAtlas: Intelligent Platform for Automated Road Defect Detection and Asset Management

no code implementations8 Sep 2021 Zhuoxiao Chen, Yiyun Zhang, Yadan Luo, Zijian Wang, Jinjiang Zhong, Anthony Southon

With the rapid development of intelligent detection algorithms based on deep learning, much progress has been made in automatic road defect recognition and road marking parsing.

Asset Management Defect Detection

Conditional Extreme Value Theory for Open Set Video Domain Adaptation

1 code implementation1 Sep 2021 Zhuoxiao Chen, Yadan Luo, Mahsa Baktashmotlagh

The majority of video domain adaptation algorithms are proposed for closed-set scenarios in which all the classes are shared among the domains.

Action Recognition Domain Adaptation +1

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