About Myself

I am currently a Ph.D. candidate in the Computer Vision and Robotic Perception (CVRP) Laboratory at National University of Singapore, under the supervision of A/P Gim Hee Lee. I worked as a computer vision algorithm engineer in Alibaba Damo Academy, and my tutors were Mr. Sun Xiuyu and Dr. Lin Ming. My research interests are machine learning and 3D computer vision, especially in neural rendering, visual perception and understanding in the real world. I received my M.S. degree in Pattern Recognition and Intelligent Systems from Beihang University, advised by Prof. Baochang Zhang.

I am seeking a summer internship at a company or an exchange opportunity at a university for 2025. If you think we are a good match, feel free to contact me!

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Featured Works

ChatSplat: 3D Conversational Gaussian Splatting

Hanlin Chen, Fangyin Wei, Gim Hee Lee
arXiv, 2024
[PDF] [Code]

VCR-GauS: View Consistent Depth-Normal Regularizer for Gaussian Surface Reconstruction

Hanlin Chen, Fangyin Wei, Chen Li, Tianxin Huang, Yunsong Wang, Gim Hee Lee
NeurIPS, 2024
[Project Page] [PDF] [Code]

FreeSplat: Generalizable 3D Gaussian Splatting Towards Free-View Synthesis of Indoor Scenes

Yunsong Wang, Tianxin Huang, Hanlin Chen, Gim Hee Lee
NeurIPS, 2024
[Project Page] [PDF] [Code]

UNIKD: UNcertainty-Filtered Incremental Knowledge Distillation for Neural Implicit Representation

Mengqi Guo, Chen Li, Hanlin Chen, Gim Hee Lee
ECCV, 2024
[Project Page] [PDF] [Code]

GOV-NeSF: Generalizable Open-Vocabulary Neural Semantic Fields

Yunsong Wang, Hanlin Chen, Gim Hee Lee
CVPR, 2024
[PDF] [Code]

NeuSG: Neural implicit surface reconstruction with 3d gaussian splatting guidance

Hanlin Chen, Chen Li, Yunsong Wang, Gim Hee Lee
arXiv, 2023
[PDF]

GNeSF: Generalizable Neural Semantic Fields

Hanlin Chen, Chen Li, Mengqi Guo, Zhiwen Yan, Gim Hee Lee
NeurIPS, 2023
[PDF] [Code]

Binarized Neural Architecture Search for Efficient Object Recognition

Hanlin Chen, Li'an Zhuo, Baochang Zhang, Xiawu Zheng, Jianzhuang Liu, Rongrong Ji, David Doermann, Guodong Guo
IJCV, 2021
[PDF]

Anti-Bandit Neural Architecture Search for Model Defense

Hanlin Chen, Baochang Zhang, Song Xue, Xuan Gong, Hong Liu, Rongrong Ji, David Doermann
ECCV, 2020
[PDF] [CODE]

Binarized Neural Architecture Search

Hanlin Chen, Li'an Zhuo, Baochang Zhang, Xiawu Zheng, Jianzhuang Liu, David Doermann, Rongrong Ji
AAAI, 2020
[PDF] [CODE]

Cogradient Descent for Bilinear Optimization

Li'an Zhuo, Baochang Zhang, Linlin Yang, Hanlin Chen, Qixiang Ye, David Doermann, Rongrong Ji, Guodong Guo
CVPR, 2020
[PDF] [CODE]

CP-NAS: Child-Parent Neural Architecture Search for 1-bit CNNs

Li'an Zhuo, Baochang Zhang, Hanlin Chen, Linlin Yang, Chen Chen, Yanjun Zhu, David Doermann
IJCAI, 2020
[PDF]

Other Publications / Preprints

• Song Xue^†, Hanlin Chen^†(co-first), Chunyu Xie, Baochang Zhang, Xuan Gong, David Doermann. Fast and Unsupervised Neural Architecture Evolution for Visual Representation Learning. IEEE Computational Intelligence Magazine, 2021.

• Hanlin Chen, Xudong Zhang, et al. Efficient Facial Landmark Localization based on Binarized Neural Networks. Electronics, 2020.

• Sheng Xu, Hanlin Chen, Kexin Liu, Jinhu Lii, Baochang Zhang, Efficient Block Pruning based on kernel and feature stabilization. Neural Computing and Applications, 2020.

• Sheng Xu, Hanlin Chen, Kexin Liu, Jinhu Lii, Baochang Zhang. Efficient Block Pruning based on kernel and feature stablization. Proceedings of Digital Image Computing: Techniques and Applications, 2019. (DICTA 2019)

• Chunlei Liu, Wenrui Ding, Yu Hu, Hanlin Chen, Baochang Zhang, Shuo Liu. Guided Convolutional Network. 13th International Conference on Distributed Smart Cameras. (ICDSC 2019)