About Me

I am a second-year Ph.D. student at the Department of Computer Science and Engineering, the Hong Kong University of Science and Technology (HKUST), supervised by Prof. Dit-Yan Yeung. Before that, I obtained a Master’s degree at Human-Cyber-Physical Intelligence Integration Lab of Sun Yat-san University in 2019, supervised by Prof. Liang Lin and Prof. Xiaodan Liang.

My current research interest are 3D generation and perception, including text-to-3D generation, scene understanding. I did some works on 2D/3D detection and representation learning.

I am looking for summer Intern! Please feel free to reach out :)

News

[02/2023]: One paper, is accepted to CVPR 2023.
[01/2023]: One paper, is accepted to ICLR 2023.
[09/2022]: I started my Ph.D. journey at HKUST.

Publications

(* indicates equal contribution)

3D Generation

JointDreamer: Ensuring Geometry Consistency and Text Congruence in Text-to-3D Generation via Joint Score Distillation: Chenhan Jiang*, Yihan Zeng*, Tianyang Hu, Songcen Xu, Wei Zhang, Dit-Yan Yeung, Hang Xu; arXiv Preprint, 2023; [Project]

Fast-T3D: Fast Text-to-3D Object Generation via Scarce 3D Prior and Multi-Gradient Optimization: Chenhan Jiang*, Yihan Zeng*, Jianhua Han, Songcen Xu, Wei Zhang, Dit-Yan Yeung, Hang Xu; arXiv Preprint, 2023

3D Representation Learning

CO³: Cooperative Unsupervised 3D Representation Learning for Autonomous Driving: Runjian Chen, Yao Mu, Runsen Xu, Wenqi Shao, Chenhan Jiang, Hang Xu, Zhenguo Li, Pin Luo; ICLR, 2023; [Paper] [Code]

CLIP²: Contrastive Language-Image-Point Pretraining from Real-World Point Cloud Data: Yihan Zeng*, Chenhan Jiang*, Jiageng Mao, Jianhua Han, Chaoqiang Ye, Qingqiu Huang, Dit-Yan Yeung, Zhen Yang, Xiaodan Liang, Hang Xu; CVPR, 2023; [Paper]

One Million Scenes for Autonomous Driving: ONCE Dataset: Jiageng Mao*, Minzhe Niu*, Chenhan Jiang, Hanxue Liang, Jingheng Chen, Xiaodan Liang, Yamin Li, Chaoqiang Ye, Wei Zhang, Zhenguo Li, Jie Yu, Chunjing Xu, Hang Xu; NeurIPS Dataset and Benchmark, 2022; [Paper] [Code]

Exploring Geometry-Aware Contrast and Clustering Harmonization for Self-supervised 3d Object Detection: Hanxue Liang*, Chenhan Jiang*, Dapeng Feng, Xin Chen, Hang Xu, Xiaodan Liang, Wei Zhang, Zhenguo Li, Luc Van Gool; ICCV, 2021; [Paper]

2D Object Detection

Deeply Unsupervised Patch Re-Identification for Pre-training Object Detectors: Jian Ding*, Enze Xie*, Hang Xu, Chenhan Jiang, Zhenguo Li, Ping Luo, Gui-Song Xia; TPAMI, 2022; [Paper] [Code]

SP-NAS: Serial-to-Parallel Backbone Search for Object Detection: Chenhan Jiang, Hang Xu, Xiaodan Liang, Wei Zhang, Zhenguo Li; CVPR, 2020; [Paper] [Code]

Spatial-Aware Graph Relation Network for Large-scale Object Detection: Hang Xu*, Chenhan Jiang*, Xiaodan Liang, Zhenguo Li; CVPR, 2019; [Paper] [Code]

Reasoning-RCNN: Unifying Adaptive Global Reasoning into Large-scale Object Detection: Hang Xu*, Chenhan Jiang*, Xiaodan Liang, Liang Lin, Zhenguo Li; CVPR, 2019; [Paper] [Code]

Hybrid Knowledge Routed Modules for Large-scale Object Detection: Chenhan Jiang*, Hang Xu*, Xiaodan Liang, Liang Lin; NeurIPS, 2018; [Paper] [Code]

Others

How to Save your Annotation Cost for Panoptic Segmentation?: Xuefeng Du, Chenhan Jiang, Hang Xu, Gengwei Zhang, Zhenguo Li; AAAI, 2021; [Paper]

Elixirnet: Relation-Aware Network Architecture Adaptation for Medical Lesion Detection: Chenhan Jiang*, Shaoju Wang*, Hang Xu, Xiaodan Liang, Nong Xiao; AAAI, 2020; [Paper]

3D Human Pose Machines with Self-Supervised Learning: Keze Wang, Liang Lin, Chenhan Jiang, Chen Qian, Pengxu Wei; TPAMI, 2019; [Paper] [Code]

Layout-Graph Reasoning for Fashion Landmark Detection: Weijiang Yu, Xiaodan Liang, Ke Gong, Chenhan Jiang, Nong Xiao, Liang Lin; CVPR, 2019; [Paper]