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cs.CV2025
Combining Discrepancy-Confusion Uncertainty and Calibration Diversity for Active Fine-Grained Image Classification
Yinghao Jin, Xi Yang
Active learning (AL) aims to build high-quality labeled datasets by iteratively selecting the most informative samples from an unlabeled pool under limited annotation budgets. Howe…
cs.CV2023
OSIS: Efficient One-stage Network for 3D Instance Segmentation
Chuan Tang, Xi Yang
Current 3D instance segmentation models generally use multi-stage methods to extract instance objects, including clustering, feature extraction, and post-processing processes. Howe…