Joint Bounding Box Regression And Class Prediction With Unified Loss Optimization

via “anchor-free bounding box regression with iou-aware loss”

object-detection model by undefined. 1,10,212 downloads.

Unique: Combines anchor-free regression with deformable attention, allowing the model to focus on relevant spatial regions for each object rather than processing fixed anchor locations. This synergy reduces the number of candidate boxes and improves regression accuracy compared to anchor-based deformable detectors.

vs others: Simpler than anchor-based methods (YOLO, Faster R-CNN) because it eliminates anchor design and matching, while achieving better box quality than L1-based regression through IoU-aware loss that directly optimizes overlap metric.