195 citations · 607 across the 22 of their papers we have counts for
7 papers · 1 filter
Point Transformer V2: Grouped Vector Attention and Partition-based Pooling
Xiaoyang Wu, Yixing Lao, Li Jiang +2
As a pioneering work exploring transformer architecture for 3D point cloud understanding, Point Transformer achieves impressive results on multiple highly competitive benchmarks. I…
MTR-A: 1st Place Solution for 2022 Waymo Open Dataset Challenge -- Motion Prediction
Shaoshuai Shi, Li Jiang, Dengxin Dai +1
In this report, we present the 1st place solution for motion prediction track in 2022 Waymo Open Dataset Challenges. We propose a novel Motion Transformer framework for multimodal…
Boosting Single-Frame 3D Object Detection by Simulating Multi-Frame Point Clouds
Wu Zheng, Li Jiang, Fanbin Lu +2
To boost a detector for single-frame 3D object detection, we present a new approach to train it to simulate features and responses following a detector trained on multi-frame point…
Boosting 3D Object Detection by Simulating Multimodality on Point Clouds
Wu Zheng, Mingxuan Hong, Li Jiang +1
This paper presents a new approach to boost a single-modality (LiDAR) 3D object detector by teaching it to simulate features and responses that follow a multi-modality (LiDAR-image…
DODA: Data-oriented Sim-to-Real Domain Adaptation for 3D Semantic Segmentation
Runyu Ding, Jihan Yang, Li Jiang +1
Deep learning approaches achieve prominent success in 3D semantic segmentation. However, collecting densely annotated real-world 3D datasets is extremely time-consuming and expensi…
Stratified Transformer for 3D Point Cloud Segmentation
Xin Lai, Jianhui Liu, Li Jiang +5
3D point cloud segmentation has made tremendous progress in recent years. Most current methods focus on aggregating local features, but fail to directly model long-range dependenci…