Jonathan Sadeghi — accepted AI-conference papers

2024

"On Calibration of Object Detectors: Pitfalls, Evaluation and Baselines"

Selim Kuzucu*, Kemal Oksuz*, Jonathan Sadeghi, Puneet Dokania

ECCV 2024oral

"Reliable usage of object detectors require them to be calibrated—a crucial problem that requires careful attention. Recent approaches towards this involve (1) designing new loss functions to obtain calibrated detectors by training them from scratch, and (2) post-hoc Temperature Scaling (TS) that le…

Cited by 4 Source ↗PDF ↗code ↗Scholar ↗

2023

Query-Based Hard-Image Retrieval for Object Detection at Test Time

Edward Ayers, Jonathan Sadeghi, John Redford, Romain Mueller, Puneet K. Dokania

AAAI 2023technical

There is a longstanding interest in capturing the error behaviour of object detectors by finding images where their performance is likely to be unsatisfactory. In real-world applications such as autonomous driving, it is also crucial to characterise potential failures beyond simple requirements of d…

Cited by 2 Source ↗PDF ↗code ↗Scholar ↗