典型文献
ARM3D:Attention-based relation module for indoor 3D object detection
文献摘要：
Relation contexts have been proved to be useful for many challenging vision tasks.In the field of 3D object detection,previous methods have been taking the advantage of context encoding,graph embedding,or explicit relation reasoning to extract relation contexts.However,there exist inevitably redundant relation contexts due to noisy or low-quality proposals.In fact,invalid relation contexts usually indicate underlying scene misunderstanding and ambiguity,which may,on the contrary,reduce the performance in complex scenes.Inspired by recent attention mechanism like Transformer,we propose a novel 3D attention-based relation module(ARM3D).It encompasses object-aware relation reasoning to extract pair-wise relation contexts among qualified proposals and an attention module to distribute attention weights towards different relation contexts.In this way,ARM3D can take full advantage of the useful relation contexts and filter those less relevant or even confusing contexts,which mitigates the ambiguity in detection.We have evaluated the effectiveness of ARM3D by plugging it into several state-of-the-art 3D object detectors and showing more accurate and robust detection results.Extensive experiments show the capability and generalization of ARM3D on 3D object detection.Our source code is available at .
文献关键词：
中图分类号：
作者姓名：
Yuqing Lan;Yao Duan;Chenyi Liu;Chenyang Zhu;Yueshan Xiong;Hui Huang;Kai Xu
作者机构：
College of Computer,National University of Defense Technology,Changsha 410073,China;Shenzhen University,Shenzhen 518061,China
文献出处：
引用格式：
[1]Yuqing Lan;Yao Duan;Chenyi Liu;Chenyang Zhu;Yueshan Xiong;Hui Huang;Kai Xu-.ARM3D:Attention-based relation module for indoor 3D object detection)[J].计算可视媒体（英文）,2022(03):395-414
A类：
ARM3D
B类：
Attention,relation,module,indoor,object,detection,Relation,contexts,have,been,proved,useful,many,challenging,vision,tasks,field,previous,methods,taking,advantage,encoding,graph,embedding,explicit,reasoning,extract,However,there,exist,inevitably,redundant,due,noisy,low,quality,proposals,fact,invalid,usually,indicate,underlying,misunderstanding,ambiguity,which,may,contrary,reduce,performance,complex,scenes,Inspired,by,recent,attention,mechanism,like,Transformer,propose,novel,It,encompasses,aware,pair,wise,among,qualified,distribute,weights,towards,different,this,way,can,take,full,filter,those,less,relevant,even,confusing,mitigates,We,evaluated,effectiveness,plugging,into,several,state,art,detectors,showing,more,accurate,robust,results,Extensive,experiments,capability,generalization,Our,source,code,available
AB值：
0.571121
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