4 citations · 10 across the 8 of their papers we have counts for
5 papers · 1 filter
Semi-supervised 3D Object Detection with PatchTeacher and PillarMix
Xiaopei Wu, Liang Peng, Liang Xie +6
Semi-supervised learning aims to leverage numerous unlabeled data to improve the model performance. Current semi-supervised 3D object detection methods typically use a teacher to g…
TASeg: Temporal Aggregation Network for LiDAR Semantic Segmentation
Xiaopei Wu, Yuenan Hou, Xiaoshui Huang +8
Training deep models for LiDAR semantic segmentation is challenging due to the inherent sparsity of point clouds. Utilizing temporal data is a natural remedy against the sparsity p…
A Comprehensive Survey on 3D Content Generation
Jian Liu, Xiaoshui Huang, Tianyu Huang +8
Recent years have witnessed remarkable advances in artificial intelligence generated content(AIGC), with diverse input modalities, e.g., text, image, video, audio and 3D. The 3D is…
NeRF-Det++: Incorporating Semantic Cues and Perspective-aware Depth Supervision for Indoor Multi-View 3D Detection
Chenxi Huang, Yuenan Hou, Weicai Ye +5
NeRF-Det has achieved impressive performance in indoor multi-view 3D detection by innovatively utilizing NeRF to enhance representation learning. Despite its notable performance, w…
Uni3D-LLM: Unifying Point Cloud Perception, Generation and Editing with Large Language Models
Dingning Liu, Xiaoshui Huang, Yuenan Hou +5
In this paper, we introduce Uni3D-LLM, a unified framework that leverages a Large Language Model (LLM) to integrate tasks of 3D perception, generation, and editing within point clo…