235 citations · 659 across the 25 of their papers we have counts for
13 papers · 1 filter
Context-Aware Transformer for 3D Point Cloud Automatic Annotation
Xiaoyan Qian, Chang Liu, Xiaojuan Qi +3
3D automatic annotation has received increased attention since manually annotating 3D point clouds is laborious. However, existing methods are usually complicated, e.g., pipelined…
Unsupervised Light Field Depth Estimation via Multi-view Feature Matching with Occlusion Prediction
Shansi Zhang, Nan Meng, Edmund Y. Lam
Depth estimation from light field (LF) images is a fundamental step for numerous applications. Recently, learning-based methods have achieved higher accuracy and efficiency than th…
LRT: An Efficient Low-Light Restoration Transformer for Dark Light Field Images
Shansi Zhang, Nan Meng, Edmund Y. Lam
Light field (LF) images containing information for multiple views have numerous applications, which can be severely affected by low-light imaging. Recent learning-based methods for…
Multimodal Transformer for Automatic 3D Annotation and Object Detection
Chang Liu, Xiaoyan Qian, Binxiao Huang +4
Despite a growing number of datasets being collected for training 3D object detection models, significant human effort is still required to annotate 3D boxes on LiDAR scans. To aut…
MAP-Gen: An Automated 3D-Box Annotation Flow with Multimodal Attention Point Generator
Chang Liu, Xiaoyan Qian, Xiaojuan Qi +3
Manually annotating 3D point clouds is laborious and costly, limiting the training data preparation for deep learning in real-world object detection. While a few previous studies t…
Point Cloud Denoising via Momentum Ascent in Gradient Fields
Yaping Zhao, Haitian Zheng, Zhongrui Wang +2
To achieve point cloud denoising, traditional methods heavily rely on geometric priors, and most learning-based approaches suffer from outliers and loss of details. Recently, the g…