FPG(Feature Pyramid Grids):特征金字塔网格来了 !性能优于FPN、NAS-FPN等金字塔网络。 作者团队:商汤&港中文(陈恺&林达华)&南洋理工大学&FAIR 该文章首发在arxiv上,新投稿于CVPR。 1 引言 特征金字塔网络已在目标检测中被广泛采用,以改进特征表示以更好地处理尺度变化。 设计思路 在本文中,作者设计了特征金字塔...
1. 设计核心： FPG的设计核心在于构建一个多路径、深度金字塔的网格结构。 每个路径自下而上独立发展，类似于主干通路，但通过多方向的横向连接将不同尺度的特征进行融合。2. 主要特点： 主干通道：借鉴了主流分类网络的多层次特征表示，用于提取基础特征。 金字塔通道：通过平行构建来增强网络的分辨率和定...
在目标检测领域，一种新型的特征金字塔网络——FPG（Feature Pyramid Grids）以其卓越的性能超越了FPN、NAS-FPN等经典架构。由商汤、港中文大学（陈恺、林达华）、南洋理工大学和FAIR团队合作研发，该技术已在CVPR上发布，展现了其在复杂性控制和性能提升方面的优势。FPG的设计核心在于构建一个多路径、深度...
Feature pyramid networkDiffusion modelResearch on identifying faulty insulators on distribution grids is a primary concern in the research community as it plays a crucial role in maintaining and servicing the electricity supply infrastructure for the public. In this paper, we propose the FGS model to...
OverFeat [47] is a first one-stage object detector that applies a CNN as a sliding window detector on an image pyramid. More recently, YOLO [41] and SSD [33] were proposed for the real-time processing. These approaches divide an image into multiple grids and predict class confidence level...
Feature Pyramid Grids (FPG) a deep multi-pathway feature pyramid network that represents the feature scale-space as a regular grid of parallel pathways fused by multi-directional lateral connections between them. FPG enriches the hierarchical feature representation built internally in the backbone pathway...
YOLO (Redmon et al., 2016) represents a typical detector of single-stage models, which divides the feature map into S×S grids and predicts the location, class, and confidence score of objects within each grid. Confidence score indicates the likelihood that a proposal contains an object. Subse...
The feature information used for detecting small and medium-sized objects are intertwined at the lower level (P2) of the FPN. Though different levels of the pyramid contain size-specific object information, current feature fusion methods usually neglect high-resolution shallow layers, resulting in dif...
The second step is keypoint-to-grid RoI feature abstraction, where we propose RoI-grid pooling module to aggregate the above keypoint features back to regular RoI grids of each proposal. It encodes multi-scale contextual information to form regular grid features for proposal...
In turn, here, we create a pyramid by splitting the image in an increasing number of grids, used to extract the finer shape information through the Zernike responses. PZOT and the methods proposed in [4] and [12] modify a 2D spatial descrip- tor to incorporate temporal information. This ...