Artificial Intelligence #research#segmentation
ActiveSAM Speeds Open-Vocabulary Segmentation 5.5x, Boosts Accuracy for Noisy-Input Domains
ActiveSAM is a training-free inference framework that improves the speed-accuracy tradeoff of open-vocabulary semantic segmentation. It achieves up to 5.5x faster inference on large-vocabulary datasets while boosting average mIoU by 1.4 points over the state-of-the-art SegEarth-OV3. The method is robust to image corruption, making it suitable for noisy real-world deployments like autonomous driving.
Jun 16, 2026 1 source