4 citations · 10 across the 8 of their papers we have counts for
8 papers
PVCap: Towards Accurate 3D Dense Captioning via PseudoCap and VoxelCapNet
Xiaopei Wu, Chenshu Hou, Liang Peng +9
3D dense captioning, an emerging vision-language task, aims to generate descriptive sentences for each object in the 3D scene. Despite the impressive results achieved by previous m…
Heterogeneous and Adept Snapshot Distillation for 3D Semantic Segmentation
Xiaopei Wu, Yuenan Hou, Junkai Xu +7
Multi-modal fusion and multi-model ensembling are prevalent in enhancing the performance of 3D semantic segmentation. Despite the impressive performance, these methods either rely…
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…
Point Cloud Pre-training with Diffusion Models
Xiao Zheng, Xiaoshui Huang, Guofeng Mei +5
Pre-training a model and then fine-tuning it on downstream tasks has demonstrated significant success in the 2D image and NLP domains. However, due to the unordered and non-uniform…