33 citations · 42 across the 3 of their papers we have counts for
4 papers
A Unified Framework with Meta-dropout for Few-shot Learning
Shaobo Lin, Xingyu Zeng, Rui Zhao
Conventional training of deep neural networks usually requires a substantial amount of data with expensive human annotations. In this paper, we utilize the idea of meta-learning to…
Rethinking Pseudo-LiDAR Representation
Xinzhu Ma, Shinan Liu, Zhiyi Xia +3
The recently proposed pseudo-LiDAR based 3D detectors greatly improve the benchmark of monocular/stereo 3D detection task. However, the underlying mechanism remains obscure to the…
Adapting Object Detectors with Conditional Domain Normalization
Peng Su, Kun Wang, Xingyu Zeng +4
Real-world object detectors are often challenged by the domain gaps between different datasets. In this work, we present the Conditional Domain Normalization (CDN) to bridge the do…
GS3D: An Efficient 3D Object Detection Framework for Autonomous Driving
Buyu Li, Wanli Ouyang, Lu Sheng +2
We present an efficient 3D object detection framework based on a single RGB image in the scenario of autonomous driving. Our efforts are put on extracting the underlying 3D informa…