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cs.CV2026

Mask What Matters: Saliency-Guided Video Self-Supervised Learning for Autonomous Driving

Christopher Lang, Alexander Braun, Abhinav Valada

Video self-supervised learning through masked spatiotemporal prediction has emerged as a promising paradigm for learning feature representations from unlabeled data. However, exist…

cs.CV2026

Spotted: Location-informed Reidentification of Hyenas and Leopards in Camera Trap Surveys

Halil Sina Kelebek, Julia Hindel, Kobus Hoffman +9

Animal re-identification (ReID) in camera-trap surveys remains challenging due to low image quality, strong variation in illumination and viewpoint, and highly imbalanced numbers o…

cs.CV2026

Streaming Gaussian Encoding for 4D Panoptic Occupancy Tracking

Maximilian Luz, Thomas Nürnberg, Yakov Miron +1

Camera-based 4D panoptic occupancy tracking (4D-POT) is a promising paradigm for holistic scene understanding from multi-view imagery, enabling joint reasoning about geometry, sema…

cs.CV2026

Latent Gaussian Splatting for 4D Panoptic Occupancy Tracking

Maximilian Luz, Rohit Mohan, Thomas Nürnberg +3

Capturing 4D spatiotemporal scene structure is crucial for the safe and reliable operation of robots in dynamic environments. However, existing approaches typically address only pa…

cs.CV2026

Joint Target-Less Intrinsic and Extrinsic Camera-LiDAR Calibration using Deep Point Correspondences

Simon Bultmann, Daniele Cattaneo, Abhinav Valada

Accurate camera-LiDAR calibration is a prerequisite for robust multi-modal perception in robotics. Recent target-less approaches based on deep point correspondences achieve remarka…

cs.CV2026

Hyp2Former: Hierarchy-Aware Hyperbolic Embeddings for Open-Set Panoptic Segmentation

Yao Lu, Rohit Mohan, Florian Drews +2

Recognizing unknown objects is crucial for safety-critical applications such as autonomous driving and robotics. Open-Set Panoptic Segmentation (OPS) aims to segment known thing an…