13 citations · 17 across the 6 of their papers we have counts for
7 papers · 1 filter
Robo-SGG: Exploiting Layout-Oriented Normalization and Restitution Can Improve Robust Scene Graph Generation
Changsheng Lv, Zijian Fu, Mengshi Qi
In this paper, we propose Robo-SGG, a plug-and-play module for robust scene graph generation (SGG). Unlike standard SGG, the robust scene graph generation aims to perform inference…
RDFC-GAN: RGB-Depth Fusion CycleGAN for Indoor Depth Completion
Haowen Wang, Zhengping Che, Yufan Yang +6
Raw depth images captured in indoor scenarios frequently exhibit extensive missing values due to the inherent limitations of the sensors and environments. For example, transparent…
SGFormer: Semantic Graph Transformer for Point Cloud-based 3D Scene Graph Generation
Changsheng Lv, Mengshi Qi, Xia Li +2
In this paper, we propose a novel model called SGFormer, Semantic Graph TransFormer for point cloud-based 3D scene graph generation. The task aims to parse a point cloud-based scen…
Unsupervised Self-Driving Attention Prediction via Uncertainty Mining and Knowledge Embedding
Pengfei Zhu, Mengshi Qi, Xia Li +2
Predicting attention regions of interest is an important yet challenging task for self-driving systems. Existing methodologies rely on large-scale labeled traffic datasets that are…
RGB-Depth Fusion GAN for Indoor Depth Completion
Haowen Wang, Mingyuan Wang, Zhengping Che +5
The raw depth image captured by the indoor depth sensor usually has an extensive range of missing depth values due to inherent limitations such as the inability to perceive transpa…
Unsupervised Domain Adaptation with Temporal-Consistent Self-Training for 3D Hand-Object Joint Reconstruction
Mengshi Qi, Edoardo Remelli, Mathieu Salzmann +1
Deep learning-solutions for hand-object 3D pose and shape estimation are now very effective when an annotated dataset is available to train them to handle the scenarios and lightin…