Xiaobao Wei

I am a first-year dual PhD student at Institute of Software, Chinese Academy of Sciences and Peking University, supervised by Prof. Hui Chen from ISCAS, Prof. Shanghang Zhang from PKU and Ming Lu from Intel Labs China. I received my B.S. in Robotics Engineering from Beihang University in 2023 and obtained Beijing Distinguished Graduate Award.

I serve as a reviewer for prestigious conferences and journals including CVPR, NeurIPS, ICME, and RA-L.

My areas of focus include neural field, 3D vision and human computer interaction.

Email  /  Github  /  Google Scholar

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S3Gaussian: Self-Supervised Street Gaussians for Autonomous Driving
Nan Huang, Xiaobao Wei, Wenzhao Zheng, Pengju An, Ming Lu, Wei Zhan, Masayoshi Tomizuka, Kurt Keutzer, Shanghang Zhang,
Paper / Code

We propose a self-supervised street Gaussian (S3Gaussian) method to decompose dynamic and static elements in driving scenes without costly annotations.

[ECCV 2024]I-MedSAM: Implicit Medical Image Segmentation with Segment Anything
Xiaobao Wei*, Jiajun Cao*, Yizhu Jin, Ming Lu, Guangyu Wang, Shanghang Zhang,
Paper / Code

We propose I-MedSAM, which leverages the benefits of both continuous representations and SAM, to obtain better cross-domain ability and accurate boundary delineation.

[Neural Networks 2024] Multi-scale full spike pattern for semantic segmentation
Qiaoyi Su, Weihua He, Xiaobao Wei, Bo Xu, Guoqi Li,
Paper / Code

We propose the multi-scale and full spike segmentation network (MFS-Seg), which is based on the deep direct trained SNN and represents the first attempt to train a deep SNN with surrogate gradients for semantic segmentation.

[CVPR 2024] NTO3D: Neural Target Object 3D Reconstruction with Segment Anything
Xiaobao Wei, Renrui Zhang, Jiarui Wu, Jiaming Li, Yandong Guo, Shanghang Zhang,
Paper / Code

We propose NTO3D, a novel high-quality Neural Target Object 3D (NTO3D) reconstruction method, which leverages the benefits of both neural field and SAM.

DiffusionTalker: Personalization and Acceleration for Speech-Driven 3D Face Diffuser
Peng Chen*, Xiaobao Wei*, Ming Lu, Yitong Zhu, Naiming Yao, Xingyu Xiao, Hui Chen,
Paper / Code

We propose DiffusionTalker, a diffusion-based method that utilizes contrastive learning to personalize 3D facial animation and knowledge distillation to accelerate 3D animation generation.

[CVPR 2023] Open-Vocabulary Point-Cloud Object Detection without 3D Annotation
Yuheng Lu*, Chenfeng Xu*, Xiaobao Wei, Xiaodong Xie, Masayoshi Tomizuka, Kurt Keutzer, Shanghang Zhang,
Paper / Code

We propose OV-3DET, which leverages advanced image/vision-language pre-trained models to achieve Open-Vocabulary 3D point-cloud DETection.

[ECCV 2022] MTTrans: Cross-domain object detection with mean teacher transformer
Jinze Yu, Jiaming Liu, Xiaobao Wei, Haoyi Zhou, Yohei Nakata, Denis Gudovskiy, Tomoyuki Okuno, Jianxin Li, Kurt Keutzer, Shanghang Zhang,
Paper / Code

We propose an end-to-end cross-domain detection Transformer based on the mean teacher framework, MTTrans, which can fully exploit unlabeled target domain data in object detection training and transfer knowledge between domains via pseudo labels.

[ICGNC 2022] Center-of-Mass-Based Robust Grasp Pose Adaptation Using RGBD Camera and Force/Torque Sensing
Shang Liu*, Xiaobao Wei*, Lulu Wang, Jing Zhang, Boyu Li, Haosong Yue,

Object dropping may occur when the robotic arm grasps objects with uneven mass distribution due to additional moments generated by objects gravity. To solve this problem, we present a novel work that does not require extra wrist and tactile sensors and large amounts of experiments for learning.

[CCC 2021] Time-varying group formation-tracking control for heterogeneous multi-agent systems with switching topologies and time-varying delays
Shiyu Zhou, Xiaobao Wei, Xiwang Dong, Yongzhao Hua, Zhang Ren,

We investigate group formation-tracking problem for heterogeneous multi-agent systems (HMASs) with both switching networks and communication delays in this paper.


NeRF for Driving Scenes
End-to-end Driving at Scale


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Last updated: Nov. 2023
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