collaborators

5 papers

cs.LG2026

Conditional Attribution for Root Cause Analysis in Time-Series Anomaly Detection

Shashank Mishra, Karan Patil, Cedric Schockaert +2

Root cause analysis (RCA) for time-series anomaly detection is critical for the reliable operation of complex real-world systems. Existing explanation methods often rely on unreali…

cs.CV2026

Conditional Compatibility Learning for Context-Dependent Anomaly Detection

Shashank Mishra, Didier Stricker, Jason Rambach

Anomaly detection usually assumes that abnormality is an intrinsic property of an observation. A defect is a defect, and a rare object is rare, regardless of where it appears. Many…

cs.CV2026

PanoSAMic: Panoramic Image Segmentation from SAM Feature Encoding and Dual View Fusion

Mahdi Chamseddine, Didier Stricker, Jason Rambach

Existing image foundation models are not optimized for spherical images having been trained primarily on perspective images. PanoSAMic integrates the pre-trained Segment Anything (…

cs.CV2026

DriverGaze360: OmniDirectional Driver Attention with Object-Level Guidance

Shreedhar Govil, Didier Stricker, Jason Rambach

Predicting driver attention is a critical problem for developing explainable autonomous driving systems and understanding driver behavior in mixed human-autonomous vehicle traffic…

cs.CV2025

IMKD: Intensity-Aware Multi-Level Knowledge Distillation for Camera-Radar Fusion

Shashank Mishra, Karan Patil, Didier Stricker +1

High-performance Radar-Camera 3D object detection can be achieved by leveraging knowledge distillation without using LiDAR at inference time. However, existing distillation methods…