Multimodal Semantic-Probabilistic Objectness for Open World Object Detection
MSPO is proposed, a lightweight semantic calibration framework that augments PROB with task-aware known-category language priors while preserving its detector architecture and incremental learning protocol and demonstrates that known-category language semantics provide an effective calibration signal for probabilistic...