collaborators

5 papers

cs.CV2026

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…

cs.CV2026

Towards Visual Query Localization in the 3D World

Liang Peng, Bohan Tan, Zhipeng Zhang +4

Visual query localization (VQL) aims to predict the spatio-temporal response of the most recent occurrence in a sequence given a query. Currently, most research focuses on visual q…

cs.CV2024

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…

cs.CV2024

PD-APE: A Parallel Decoding Framework with Adaptive Position Encoding for 3D Visual Grounding

Chenshu Hou, Liang Peng, Xiaopei Wu +2

3D visual grounding aims to identify objects in 3D point cloud scenes that match specific natural language descriptions. This requires the model to not only focus on the target obj…

cs.CV2024

Pseudo Label Refinery for Unsupervised Domain Adaptation on Cross-dataset 3D Object Detection

Zhanwei Zhang, Minghao Chen, Shuai Xiao +7

Recent self-training techniques have shown notable improvements in unsupervised domain adaptation for 3D object detection (3D UDA). These techniques typically select pseudo labels,…