最近,《Towards open world object detection》的工作引入了一种基于 two-stage Faster RCNN pipeline 的开放世界目标检测器 ORE。由于在开放世界范式的训练过程中,未知目标的注释不可用,ORE 建议利用一个自动标注步骤来获得一组用于训练的 pseudo-unknowns。自动标注是由区域建议网络 (RPF) 输出的类无关建议来...
文章提出了一种开放世界目标检测(Open World Object Detection),该模型的任务是: 1.在没有明确标注时,把识别到的无法分辨类别的物体标注为“未知”; 2.当对应标签逐渐加入后,逐渐地学习已引入的“未知”目标的类别,且不遗忘之前学习到的类别信息。 同时引入一个强大的评估协议并且提供了一个创新性的解决方案,称之...
Open World Object Detection is a computer vision problem where a model is tasked to: 1) identify objects that have not been introduced to it as `unknown', without explicit supervision to do so, and 2) incrementally learn these identified unknown categories without forgetting previously learned ...
首先基于一个现象:人类在对事物进行观察的时候,是能够检测到每个实例,并按照自己已知的知识来对每个实例进行分类,有认知的归属到对应类别,无认知的归属到未知(unknown),而过往的深度学习检测任务所完成的工作只能对已有认知的实例进行定位和分类,所以作者提出,能否使得检测算法达到更近似人类的认知体验?所以作者提出了“...
Object detection is integral to a bevy of real-world applications, from robotics to medical image analysis. To be used reliably in such applications, models must be capable of handling unexpected - or novel - objects. The open world object detection (OWD) paradigm addresses this challenge by en...
论文阅读:Towards Open World Object Detection 本篇文章是今年cvpr的oral,如有理解不当,欢迎各位大佬指正。 motivation 人类可以凭借直觉从环境中找出不认识的物体,当学习到相应的知识后,人们就会了解这些物体。因此作者提出一个开放世界目标检测(Open World Object Detection)任务: 能够检测出当前没有没有标注过的物体...
Towards Open World Object Detection 代码 什么是开放世界中的目标检测呢? 1.在没有明确监督的情况下,将未被引入的对象识别为“未知”。 2.当逐步接收到相应的标签时,在不忘记之前学习过的类的情况下,逐步学习这些已识别的未知类别。 图中展示了每一个增量学习的步骤,模型识别出那些未知的目标(“?”)。这些未...
Open-world object detection (OWOD) is a challenging computer vision problem, where the task is to detect a known set of object categories while simultaneously identifying unknown objects. Additionally, the model must incrementally learn new classes that become known in the next training episodes. Dis...
1, Open World object detection is un- explored, owing to the difficulty of the problem setting. The advances in Open Set and Open World image clas- sification cannot be trivially adapted to Open Set and Open World object detection, because of a fundamental difference in the problem setting:...
最近开始接触自动驾驶场景中的hardcase挖掘工作,在学术界比较相关的就是开放世界的一系列任务,例如Out-of-distribution Detection, Anomaly Detection等等,在目标检测任务中,出现了Open-world Object Detectio…