CalibFree enables calibration-free multi-camera tracking via self-supervised feature separation through single-view distillation and cross-view reconstruction, reporting 3% higher accuracy and 7.5% better F1 on tested datasets.
ICLR (2021)
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DBMF integrates scores from text-image and vision branches to improve out-of-distribution detection on endoscopic datasets by up to 24.84% over prior methods.
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CalibFree: Self-Supervised View Feature Separation for Calibration-Free Multi-Camera Multi-Object Tracking
CalibFree enables calibration-free multi-camera tracking via self-supervised feature separation through single-view distillation and cross-view reconstruction, reporting 3% higher accuracy and 7.5% better F1 on tested datasets.
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DBMF: A Dual-Branch Multimodal Framework for Out-of-Distribution Detection
DBMF integrates scores from text-image and vision branches to improve out-of-distribution detection on endoscopic datasets by up to 24.84% over prior methods.