DAFNe: A One-Stage Anchor-Free Approach for Oriented Object Detection
We present DAFNe, a Dense one-stage Anchor-Free deep Network for oriented object detection. As a one-stage model, it performs bounding box predictions on a dense grid over the input image, being architecturally simpler in design, as well as easier to optimize than its two-stage counterparts. Furthermore, as an anchor-free model, it reduces the prediction complexity by refraining from employing bounding box anchors. With DAFNe we introduce an orientation-aware generalization of the center-ness function for arbitrarily oriented bounding boxes to down-weight low-quality predictions and a center-to-corner bounding box prediction strategy that improves object localization performance. Our experiments show that DAFNe outperforms all previous one-stage anchor-free models on DOTA 1.0, DOTA 1.5, and UCAS-AOD and is on par with the best models on HRSC2016.
Code (1)
Tasks
object-detectionObject DetectionObject LocalizationOne-stage Anchor-free Oriented Object DetectionOriented Object DetectionMethods 이 논문이 사용한 방법론
Similar Papers 제목 키워드 기반
HA-RDet: Hybrid Anchor Rotation Detector for Oriented Object Detection
Oriented object detection in aerial images poses a significant challenge due to their varying sizes and orientations. Current state-of-the-art detectors typically rely on either two-stage or one-stage approaches, often e…
object-detectionObject DetectionObject Detection In Aerial ImagesOriented Object DetectionOriented Objects as pairs of Middle Lines
The detection of oriented objects is frequently appeared in the field of natural scene text detection as well as object detection in aerial images. Traditional detectors for oriented objects are common to rotate anchors …
object-detectionObject DetectionObject Detection In Aerial ImagesOne-stage Anchor-free Oriented Object Detection+3IENet: Interacting Embranchment One Stage Anchor Free Detector for Orientation Aerial Object Detection
Object detection in aerial images is a challenging task due to the lack of visible features and variant orientation of objects. Significant progress has been made recently for predicting targets from aerial images with h…
Objectobject-detectionObject DetectionObject Detection In Aerial Images+3Deep Anatomical Federated Network (Dafne): An open client-server framework for the continuous, collaborative improvement of deep learning-based medical image segmentation
Purpose: To present and evaluate Dafne (deep anatomical federated network), a freely available decentralized, collaborative deep learning system for the semantic segmentation of radiological images through federated incr…
DiagnosticImage SegmentationIncremental LearningMedical Image Segmentation+2FCOSR: A Simple Anchor-free Rotated Detector for Aerial Object Detection
Existing anchor-base oriented object detection methods have achieved amazing results, but these methods require some manual preset boxes, which introduces additional hyperparameters and calculations. The existing anchor-…
object-detectionObject DetectionOriented Object Detection