229 citations · 1k across the 84 of their papers we have counts for
14 papers · 1 filter
Leveraging Vision-Based Point Cloud Map Priors for Camera-Based 3D Object Detection and Online Vectorized HD Mapping
Markus Käppeler, Rohit Mohan, Abhinav Valada
Camera-based 3D object detection and online vectorized HD mapping provide compact scene representations for autonomous driving, but both depend on accurate metric geometry and rema…
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…
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…
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…
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…
AnchorD: Metric Grounding of Monocular Depth Using Factor Graphs
Simon Dorer, Martin Büchner, Nick Heppert +1
Dense and accurate depth estimation is essential for robotic manipulation, grasping, and navigation, yet currently available depth sensors are prone to errors on transparent, specu…
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…
Leveraging Previous-Traversal Point Cloud Map Priors for Camera-Based 3D Object Detection and Tracking
Markus Käppeler, Özgün Çiçek, Yakov Miron +1
Camera-based 3D object detection and tracking are central to autonomous driving, yet precise 3D object localization remains fundamentally constrained by depth ambiguity when no exp…
Multi-Modal Sensor Fusion using Hybrid Attention for Autonomous Driving
Mayank Mayank, Bharanidhar Duraisamy, Florian Geiß +1
Accurate 3D object detection for autonomous driving requires complementary sensors. Cameras provide dense semantics but unreliable depth, while millimeter-wave radar offers precise…
Assessing Multimodal Chronic Wound Embeddings with Expert Triplet Agreement
Fabian Kabus, Julia Hindel, Jelena Bratulić +6
Recessive dystrophic epidermolysis bullosa (RDEB) is a rare genetic skin disorder for which clinicians greatly benefit from finding similar cases using images and clinical text. Ho…
Embedding interpretable -regression into neural networks for uncovering temporal structure in cell imaging
Fabian Kabus, Maren Hackenberg, Julia Hindel +6
While artificial neural networks excel in unsupervised learning of non-sparse structure, classical statistical regression techniques offer better interpretability, in particular wh…
Effort-Based Criticality Metrics for Evaluating 3D Perception Errors in Autonomous Driving
Sharang Kaul, Simon Bultmann, Mario Berk +1
Criticality metrics such as time-to-collision (TTC) quantify collision urgency but do not distinguish the operational consequences of false-positive (FP) and false-negative (FN) pe…
ForecastOcc: Vision-based Semantic Occupancy Forecasting
Riya Mohan, Juana Valeria Hurtado, Rohit Mohan +1
Autonomous driving requires forecasting both geometry and semantics over time to effectively reason about future environment states. Existing vision-based occupancy forecasting met…
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…