Human-Object Interaction (HOI) detection plays a core role in activity understanding. As compositional learning problem (human-verb-object), studying its generalization matters. However, widely-used metric mean average precision (mAP) fails to model the well. Thus, we propose novel metric, mPD (mean Performance Degradation), as complementary of mAP evaluate performance gap among compositions di...

Simultaneous localization and mapping (SLAM) based on RGB-D cameras has been widely used for robot navigation in unknown environments. Most current SLAM methods are constrained by static environment assumptions perform poorly real-world dynamic scenarios. To improve the robustness performance of systems environments, this paper proposes a new method indoor scenes object detection. The presented...

Regional landslide identification is important for the risk management of hazards. The traditional methods regional were mainly conducted by a human being. In previous studies, automatic recognition focused on new landslides distinct from environment induced rainfall or earthquake, using image classification method and semantic segmentation deep learning. However, there lack research old loess ...

Object instance detection finds where a specific object instance is in an image or a video frame. It is a variation of object detection, but distinguished on two points. First, object detection focused on a category of object, while object instance detection focused on a specific object. For instance, object detection may work to find where toothpaste is in an image, while object instance detec...

Object detection is one of the major challenges in visual sensor networks (VSNs) which is set up in the monitoring applications. Many approaches proposed to solve the object detection problem in VSNs, considering diverse metrics such as reliability, energy consumption, detection accuracy and being realtime. In this paper, a survey on the object detection methods in visual sensor networks is pre...

Object detection, a fundamental duty in computer vision that has wide range of practical applications, they are surveillance, robotics, and autonomous driving. Recent developments deep learning have got gradual improvemenrts detection accuracy speed. One the most popular effective models for object is YOLOv5. In this discussion, we an model through YOLOv5 its implementation tasks. We discuss mo...