arXiv:1512.03424
Evaluation of Object Detection Proposals Under Condition Variations
원문 초록
Object detection is a fundamental task in many computer vision applications, therefore the importance of evaluating the quality of object detection is well acknowledged in this domain. This process gives insight into the capabilities of methods in handling environmental changes. In this paper, a new method for object detection is introduced that combines the Selective Search and EdgeBoxes. We tested these three methods under environmental variations. Our experiments demonstrate the outperformance of the combination method under illumination and view point variations.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Towards Reliable Detection of Empty Space: Conditional Marked Point Processes for Object Detection
Multiple Object Stitching for Unsupervised Representation Learning
Domain Randomization for Object Detection in Manufacturing Applications using Synthetic Data: A Comprehensive Study
Edge-Enabled Collaborative Object Detection for Real-Time Multi-Vehicle Perception
Multispectral Detection Transformer with Infrared-Centric Sensor Fusion
A Real-Time System for Egocentric Hand-Object Interaction Detection in Industrial Domains
토론
이 논문과 연결된 포럼 글이 아직 없습니다.