no code implementations • 18 Mar 2024 • Sha Zhang, Di Huang, Jiajun Deng, Shixiang Tang, Wanli Ouyang, Tong He, Yanyong Zhang
The ability to understand and reason the 3D real world is a crucial milestone towards artificial general intelligence.
1 code implementation • 18 Mar 2024 • Sha Zhang, Jiajun Deng, Lei Bai, Houqiang Li, Wanli Ouyang, Yanyong Zhang
We present a hybrid-view-based knowledge distillation framework, termed HVDistill, to guide the feature learning of a point cloud neural network with a pre-trained image network in an unsupervised man- ner.
no code implementations • 14 Mar 2024 • Jiajun Deng, Sha Zhang, Feras Dayoub, Wanli Ouyang, Yanyong Zhang, Ian Reid
In this work, we present PoIFusion, a simple yet effective multi-modal 3D object detection framework to fuse the information of RGB images and LiDAR point clouds at the point of interest (abbreviated as PoI).
1 code implementation • 12 Oct 2023 • Haoyi Zhu, Honghui Yang, Xiaoyang Wu, Di Huang, Sha Zhang, Xianglong He, Hengshuang Zhao, Chunhua Shen, Yu Qiao, Tong He, Wanli Ouyang
In this paper, we introduce a novel universal 3D pre-training framework designed to facilitate the acquisition of efficient 3D representation, thereby establishing a pathway to 3D foundational models.
Ranked #1 on 3D Semantic Segmentation on ScanNet++ (using extra training data)
1 code implementation • 12 Oct 2023 • Honghui Yang, Sha Zhang, Di Huang, Xiaoyang Wu, Haoyi Zhu, Tong He, Shixiang Tang, Hengshuang Zhao, Qibo Qiu, Binbin Lin, Xiaofei He, Wanli Ouyang
In the context of autonomous driving, the significance of effective feature learning is widely acknowledged.
no code implementations • 4 Feb 2023 • Haojie Ren, Sha Zhang, Sugang Li, Yao Li, Xinchen Li, Jianmin Ji, Yu Zhang, Yanyong Zhang
In this paper, we propose TrajMatch -- the first system that can automatically calibrate for roadside LiDARs in both time and space.