Small object detection in aerial imagery presents significant challenges in computer vision due to the minimal data inherent in small-sized objects and their propensity to be obscured by larger objects and background noise. Traditional methods using transformer-based models often face limitations stemming...
We then train a YOLOv4 model for a two-stage detection process: First, the context is recognized, then the small object of interest is detected. We evaluate our pipeline on the augmented reality device Microsoft Hololens 2. PDF Paper record ...
Object detection has been widely applied in various fields with the rapid development of deep learning in recent years. However, detecting small objects is still a challenging task because of the limited information in features and the complex background. To further enhance the detection accuracy of...
This paper addresses the problem of exploiting spatiotemporal information to improve small object detection precision in video. We propose a two-stage obje
链接:https://openaccess.thecvf.com/content/CVPR2022/papers/Yang_QueryDet_Cascaded_Sparse_Query_for_Accelerating_High-Resolution_Small_Object_Detection_CVPR_2022_paper.pd 摘要:虽然深度学习的一般目标检测在过去几年取得了很大的成功,但小目标检测的性能和效率还远远不能令人满意。促进小目标检测最常见和有效的...
In this paper, we give a comprehensive survey of recent advances in visual object detection with deep learning. By reviewing a large body of recent related work in literature, we systematically analyze the existing object detection frameworks and organize the survey into three major parts: (i) ...
The parameter count of existing models for small object detection limits their applicability on resource-constrained devices. To address these challenges, this paper introduces a detail-enhanced lightweight network (DDCNet) for small object detection. DDCNet incorporates a detail feature compensation ...
This paper use GAN to handle the issue of small object detection which is a very hard problem in general object detection. As shown in the following figures, small object and large objects usually shown different representations from the feature level. ...
Object detection has been a building block in computer vision. Though considerable progress has been made, there still exist challenges for objects with small size, arbitrary direction, and dense distribution. Apart from natural images, such issues are especially pronounced for aerial images of great...
Paper Code NewsClaims: A New Benchmark for Claim Detection from News with Attribute Knowledge 2 code implementations • 16 Dec 2021 • Revanth Gangi Reddy, Sai Chetan, Zhenhailong Wang, Yi R. Fung, Kathryn Conger, Ahmed Elsayed, Martha Palmer, Preslav Nakov, Eduard Hovy, Kevin Small, ...