2020年10月24日 · In this paper, we propose a low-level sensor fusion 3D object detector that combines two Region of Interest (RoI) from radar and camera feature maps by a Gated RoI Fusion (GRIF) to perform robust vehicle detection.

2025年1月29日 · 不像常规的cancatenation或者element-wise相加/求平均的融合方式，作者使用了gated region of interest fusion (GRIF)的方法. GRIF将radar和image对应roi区域的features concate起来，通过卷积生成2个权重。 基于这2个权重对相关roi区域的radar features和image features进行加权求和来进行融合。 思想类似于SeNet中的attention思路，让网络自适应的学会调整不同roi区域中两个不同features的权重。 因为单帧radar点云比较稀疏。 作者通过积累6帧、 …

2020年10月25日 · In this paper, we propose a low-level sensor fusion 3D object detector that combines two Region of Interest (RoI) from radar and camera feature maps by a Gated RoI Fusion (GRIF) to perform...

from radar and camera feature maps by a Gated RoI Fusion (GRIF) to perform robust vehicle detection. To take advantage of sensors and utilize a sparse radar point cloud, we design a GRIF that employs the explicit gating mechanism to adaptively select the approp riate data when one of the sensors is abnormal.

In this paper, we propose a low-level sensor fusion 3D object detector that combines two Region of Interest (RoI) from radar and camera feature maps by a Gated RoI Fusion (GRIF) to perform robust vehicle detection.

aspiring filmmaker

GRIF adaptively combines RoI features to robustly predict the class probability and 3D box.

Contact Uploading & Non-Users. Meta Verified. English

Exploring light transitions through defective glass, as the colors fail to converge at one focus through the lens, the spectrum splits, causing beautiful emissions of hues & tones. The glass …

Make games, stories and interactive art with Scratch. (scratch.mit.edu)