Most of the existing works either predict one of these 3D properties or focus on solving both for a single object. One fundamental challenge lies in how to learn an effective representation of the image that is well-suited for 3D detection and reconstruction. In this work, we propose to ...
Infrared object detection constitutes a significant ship-targeting methodology, exerting a vital role in maritime safety. The contemporary research regarding infrared ship imagery is insufficient and remains in need of addressing the issues related to smaller object sizes and more elaborate information. To...
C signify a class. C1 is house and C 2 is tree. If there is no house and there is a tree, it is 0 and 1. But this object localization is for a single object at a image. If there are multiple object to localize on an image, we use multiple object detection. As like the objec...
Physical adversarial attacks in object detection have attracted increasing attention. However, most previous works focus on hiding the objects from the detector by generating an individual adversarial patch, which only covers the planar ... D Wang,T Jiang,J Sun,... 被引量: 0发表: 2021年 Multi...
In fact, it is no doubt that a multiple object tracker can be realized with multiple single ones Background# The spirit of our approach, that learning auxiliary associative embeddings simultaneously with the main task, also shows good performance in many other vision tasks SOT and MOT# SOT di...
While benchmarking single object trackers is rather straightforward, measuring the performance of multiple object trackers needs careful design as multiple correspondence constellations can arise (see image below). A variety of methods have been proposed in the past and while there is no general ...
OpenMMLab Video Perception Toolbox. It supports Video Object Detection (VID), Multiple Object Tracking (MOT), Single Object Tracking (SOT), Video Instance Segmentation (VIS) with a unified framework. - GitHub - waynelwz/mmtracking: OpenMMLab Video Percep
对于一个分类网络,在测试阶段,使用single crop/multiple crop得到的结果是不一样的,相当于将测试图像做数据增强。 shicaiyang(星空下的巫师)说[1],训练的时候当然随机剪裁,但测试的时候有技巧: 单纯将测试图像resize到某个尺度(例如256xN),选择其中center crop(即图像正中间区域,比如224x224),作为CNN的输入,去评...
Multiple images are utilized to per- form co-saliency in [3] but they are mostly focused on the single-class unsupervised co-segmentation task rather than localizing and learning multiple object models. Despite the substantial interests in computer vision, saliency detection has received relatively ...
Vision’s own object detection algorithms. For example, the Vision framework’sVNImageRequestHandleraccepts face detection, text detection, and barcode detection requests, and those requests return their results in subclasses ofVNObservation. You can pass these observations directly intoVNTrackObjectRequest...