Centralized Feature Pyramid for Object Detection
Nanjing University of Science and Technology · Hong Kong University of Science and Technology · +1 more institution
Abstract
The visual feature pyramid has shown its superiority in both effectiveness and efficiency in a variety of applications. However, current methods overly focus on inter-layer feature interactions while disregarding the importance of intra-layer feature regulation. Despite some attempts to learn a compact intra-layer feature representation with the use of attention mechanisms or vision transformers, they overlook the crucial corner regions that are essential for dense prediction tasks. To address this problem, we propose a Centralized Feature Pyramid (CFP) network for object detection, which is based on a globally explicit centralized feature regulation. Specifically, we first propose a spatial explicit visual…
Citation impact
- FWCI
- 35.78
- Percentile
- 100%
- References
- 95
Authors
4Topics & keywords
- Feature (linguistics)
- Computer science
- Pyramid (geometry)
- Artificial intelligence
- Object detection
- Discriminative model
- Pattern recognition (psychology)
- Feature extraction
- Reduced inequalities