🔥 News
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2024.10: 🎉🎉 I recieve the national scholarship.
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2024.09: 🎉🎉 Two papers (AdaptiveDiffusion and 3DET-Mamba) are accepted by NeurIPS 2024. One is about training-free acceleration of diffusion model, another is about mamba architecture in 3D detection.
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2024.07: 🎉🎉 One paper (Reg-TTA3D) is accepted by ECCV 2024. We explore test-time adaptive 3d object detection for the first time.
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2024.01: 🎉🎉 One paper (ReSimAD) is accepted by ICLR 2024. We propose a zero-shot generalization framework by reconstructing mesh and simulating target point clouds.
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2023.09: 🎉🎉 One Paper (AD-PT) is accepted by NeurIPS 2023.We explore 3D pre-training pipeline to obtain backbones with strong generalization capability.
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2023.02: 🎉🎉 Two Papers (Bi3D and Uni3D) are accepted by CVPR 2023. One is about active domain adaptation for 3D object detection, another is about multi-dataset training for 3d object detection.
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2022.07: 🎉🎉 One Paper (HelixFormer) is accepted by ACM'MM 2022. We explore Transformer architecture on few-shot fine-grained classification task.
📝 Publications
Training-Free Adaptive Diffusion with Bounded Difference Approximation Strategy
Hancheng Ye*, Jiakang Yuan*, Renqiu Xia, Xiangchao Yan, Tao Chen, Junchi Yan, Botian Shi, Bo Zhang
- Propose AdaptiveDiffusion to adaptively reduce the noise prediction steps during the denoising proces guided by the third-order latent difference.
3DET-Mamba: State Space Model for End-to-End 3D Object Detection
Mingsheng Li*, Jiakang Yuan*, Sijin Chen, Lin Zhang, Anyu Zhu, Xin Chen, Tao Chen
- Exploit the potential of Mamba architecture on 3D scene-level perception for the first time.
Reg-TTA3D: Better Regression Makes Better Test-time Adaptive 3D Object Detection
Jiakang Yuan, Bo Zhang, Kaixiong Gong, Xiangyu Yue, Botian Shi, Yu Qiao, Tao Chen
- Explore a new task named test-time domain adaptive 3D object detection and propose a pseudo-label-based test-time adaptative 3D object detection method.
Bo Zhang*, Xinyu Cai*, Jiakang Yuan, Donglin Yang, Jianfei Guo, Xiangchao Yan, Renqiu Xia, Botian Shi, Min Dou, Tao Chen, Si Liu, Junchi Yan, Yu Qiao
- Provide a new perspective and approach of alleviating the domain shifts, by proposing a Reconstruction-Simulation-Perception scheme.
AD-PT: Autonomous Driving Pre-Training with Large-scale Point Cloud Dataset
Jiakang Yuan, Bo Zhang, Xiangchao Yan, Tao Chen, Botian Shi, Yikang Li, Yu Qiao
- Build a large-scale pre-training point-cloud dataset with diverse data distribution, and meanwhile learn generalizable representations.
Bi3D: Bi-domain Active Learning for Cross-domain 3D Object Detection
Jiakang Yuan, Bo Zhang, Xiangchao Yan, Tao Chen, Botian Shi, Yikang Li, Yu Qiao
- Propose a Bi-domain active learning approach which select samples from both source and target domain to solve the cross-domain 3D object detection task.
Uni3D: A Unified Baseline for Multi-dataset 3D Object Detection
Bo Zhang, Jiakang Yuan, Botian Shi, Tao Chen, Yikang Li, Yu Qiao
- Present a Uni3D which tackle multi-dataset 3D object detection from data-level and semantic-level.
Bo Zhang*, Jiakang Yuan*, Baopu Li, Tao Chen, Jiayuan Fan, Botian Shi
- Propose a Transformer-based double-helix model to achieve the cross-image object semantic relation mining in a bidirectional and symmetrical manner.
📖 Educations
- 2022.09 - Now, Ph.D. Candidate, School of Information Science and Technology, Fudan University.
- 2018.06 - 2022.06, Bachelor Degree, School of Information Science and Technology, Fudan University.
💬 Invited Talks
- 2023.09, Invited talk of Effcient Pre-training of Autonomous Driving. [Video]
- 2023.07, Invited talk of Towards 3D General Representation at Techbeat. [Video]
- 2023.03, Invited talk of Transferable of Autonomous Driving. [Video]
💻 Internships
- 2024.10 - Now, Shanghai AI Laboratory, China.
- 2022.08 - 2024.02, Shanghai AI Laboratory, China.
📝 Academic Services
- Reviewer of CVPR, ICML, ICLR, ECCV, T-CSVT, T-MM.