34 citations · 143 across the 20 of their papers we have counts for
16 papers · 1 filter
Is Synthetic Data From Diffusion Models Ready for Knowledge Distillation?
Zheng Li, Yuxuan Li, Penghai Zhao +3
Diffusion models have recently achieved astonishing performance in generating high-fidelity photo-realistic images. Given their huge success, it is still unclear whether synthetic…
Self-Supervised 3D Scene Flow Estimation Guided by Superpoints
Yaqi Shen, Le Hui, Jin Xie +1
3D scene flow estimation aims to estimate point-wise motions between two consecutive frames of point clouds. Superpoints, i.e., points with similar geometric features, are usually…
Refined Response Distillation for Class-Incremental Player Detection
Liang Bai, Hangjie Yuan, Tao Feng +2
Detecting players from sports broadcast videos is essential for intelligent event analysis. However, existing methods assume fixed player categories, incapably accommodating the re…
Curricular Object Manipulation in LiDAR-based Object Detection
Ziyue Zhu, Qiang Meng, Xiao Wang +3
This paper explores the potential of curriculum learning in LiDAR-based 3D object detection by proposing a curricular object manipulation (COM) framework. The framework embeds the…
Robust Outlier Rejection for 3D Registration with Variational Bayes
Haobo Jiang, Zheng Dang, Zhen Wei +3
Learning-based outlier (mismatched correspondence) rejection for robust 3D registration generally formulates the outlier removal as an inlier/outlier classification problem. The co…
3D-Aware Multi-Class Image-to-Image Translation with NeRFs
Senmao Li, Joost van de Weijer, Yaxing Wang +3
Recent advances in 3D-aware generative models (3D-aware GANs) combined with Neural Radiance Fields (NeRF) have achieved impressive results. However no prior works investigate 3D-aw…