59 citations · 113 across the 9 of their papers we have counts for
13 papers
MonoDistill: Learning Spatial Features for Monocular 3D Object Detection
Zhiyu Chong, Xinzhu Ma, Hong Zhang +4
3D object detection is a fundamental and challenging task for 3D scene understanding, and the monocular-based methods can serve as an economical alternative to the stereo-based or…
An Underwater Image Semantic Segmentation Method Focusing on Boundaries and a Real Underwater Scene Semantic Segmentation Dataset
Zhiwei Ma, Haojie Li, Zhihui Wang +5
With the development of underwater object grabbing technology, underwater object recognition and segmentation of high accuracy has become a challenge. The existing underwater objec…
Delving into Localization Errors for Monocular 3D Object Detection
Xinzhu Ma, Yinmin Zhang, Dan Xu +4
Estimating 3D bounding boxes from monocular images is an essential component in autonomous driving, while accurate 3D object detection from this kind of data is very challenging. I…
A Unified Joint Maximum Mean Discrepancy for Domain Adaptation
Wei Wang, Baopu Li, Shuhui Yang +6
Domain adaptation has received a lot of attention in recent years, and many algorithms have been proposed with impressive progress. However, it is still not fully explored concerni…
Full Matching on Low Resolution for Disparity Estimation
Hong Zhang, Shenglun Chen, Zhihui Wang +2
A Multistage Full Matching disparity estimation scheme (MFM) is proposed in this work. We demonstrate that decouple all similarity scores directly from the low-resolution 4D volume…
Direct Depth Learning Network for Stereo Matching
Hong Zhang, Haojie Li, Shenglun Chen +4
Being a crucial task of autonomous driving, Stereo matching has made great progress in recent years. Existing stereo matching methods estimate disparity instead of depth. They trea…