\quad 开放集目标检测(Open-Set Object Detection): OV-DETR和ViLD:OV-DETR和ViLD分别利用CLIP模型的图像和文本嵌入作为查询,在DETR框架中解码特定类别的盒子;ViLD则是从CLIP教师模型中提取知识到R-CNN式检测器中,以便学习的区域嵌入包含语言的语义。 GLIP的贡献:GLIP将对象检测定义为地面问题,利用额外的地面数据帮...
在之前的 open-set object detection (OSOD) 中,除了检测识别已知物体外,还会检测一些未知类别的物体,但把所有未知的物体都归到 “未知类”。该论文提出的 Open-Set Object Detection and Discovery (OSODD),不仅可以检测未知物体,还可以挖掘它们潜在的类别。OSODD 采用了两阶检测方式,先对已知物体和未知物体进行...
在之前的 open-set object detection (OSOD) 中,除了检测识别已知物体外,还会检测一些未知类别的物体,但把所有未知的物体都归到 “未知类”。该论文提出的 Open-Set Object Detection and Discovery (OSODD),不仅可以检测未知物体,还可以挖掘它们潜在的类别。OSODD 采用了两阶检测方式,先对已知物体和未知物体进行...
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3 Formalizing Open-Set Object Detection 形式化开集目标检测 在不属于任一训练集中已有类的实例上测试系统的场景定义为开集。因此,根据定义,目标检测器只能检测它们被训练来识别的物体,而拒绝其他物体,我们认为目标检测是一个普遍的开放集问题。虽然根据上述定义及开集分类问题,可以给开集目标检测下一个定义,但是我们要...
Open-set object detection better simulates the real world compared with close-set object detection. Besides the classes of interest, it also pays attention to unknown objects in the environment. We extend the previous concept of open-set object detection, aiming to detect both known and unknown ...
大多数的现有方法均集中于研究分类问题,即Cross-Domain Few-Shot Classification, 但是同样很重要的物体检测任务(Object Detection,OD)却很少被研究,这促使了我们想要探究OD问题在跨域小样本的情况下是否也会遭遇挑战,以及是否会存在跟分类任务表现出不同的特性。
In this paper, we develop an open-set object detector, called Grounding DINO, by marrying Transformer-based detector DINO with grounded pre-training, which can detect arbitrary objects with human inputs such as category names or referring...
In this paper, we seek a solution for the generalized few-shot open-set object detection (G-FOOD), which aims to avoid detecting unknown classes as known classes with a high confidence score while maintaining the performance of few-shot detection. ...
The DOSOD package is an example of quantized deployment based on Decoupled Open-Set Object Detector. The image data comes from local image feedback and subscribed image messages. Additionally, DOSOD supports custom detection categories detect, which is the biggest difference with conventional detector....