4 citations · 4 across the 7 of their papers we have counts for
8 papers
MultiFly: A Real-World Multimodal Aerial Dataset with Annotation-Efficient Label Transfer and Cross-Modal Semantic Consistency
Markus Gross, Andreas Greiner, Taehyoung Kim +12
We introduce MultiFly, a real-world, low-altitude UAV dataset for semantic perception across RGB, thermal, LiDAR, and radar modalities. MultiFly provides 17,272 synchronized sample…
GMT: Goal-Conditioned Multimodal Transformer for 6-DOF Object Trajectory Synthesis in 3D Scenes
Huajian Zeng, Abhishek Saroha, Daniel Cremers +1
Synthesizing controllable 6-DOF object manipulation trajectories in 3D environments is essential for enabling robots to interact with complex scenes, yet remains challenging due to…
SegFly: A Dataset and 2D-3D-2D Paradigm for Aerial RGB-Thermal Semantic Segmentation at Scale
Markus Gross, Sai Bharadhwaj Matha, Rui Song +4
Semantic segmentation for uncrewed aerial vehicles (UAVs) is fundamental for aerial scene understanding, yet existing RGB and RGB-T datasets remain limited in scale, diversity, and…
SafeLand: Safe Autonomous Landing in Unknown Environments with Bayesian Semantic Mapping
Markus Gross, Andreas Greiner, Sai Bharadhwaj Matha +3
Autonomous landing of uncrewed aerial vehicles (UAVs) in unknown, dynamic environments poses significant safety challenges, particularly near people and infrastructure, as UAVs tra…
DrivIng: A Large-Scale Multimodal Driving Dataset with Full Digital Twin Integration
Dominik Rößle, Xujun Xie, Adithya Mohan +3
Perception is a cornerstone of autonomous driving, enabling vehicles to understand their surroundings and make safe, reliable decisions. Developing robust perception algorithms req…
UrbanIng-V2X: A Large-Scale Multi-Vehicle, Multi-Infrastructure Dataset Across Multiple Intersections for Cooperative Perception
Karthikeyan Chandra Sekaran, Markus Geisler, Dominik Rößle +6
Recent cooperative perception datasets have played a crucial role in advancing smart mobility applications by enabling information exchange between intelligent agents, helping to o…
Advancing Robustness in Deep Reinforcement Learning with an Ensemble Defense Approach
Adithya Mohan, Dominik Rößle, Daniel Cremers +1
Recent advancements in Deep Reinforcement Learning (DRL) have demonstrated its applicability across various domains, including robotics, healthcare, energy optimization, and autono…
Unlocking Past Information: Temporal Embeddings in Cooperative Bird's Eye View Prediction
Dominik Rößle, Jeremias Gerner, Klaus Bogenberger +3
Accurate and comprehensive semantic segmentation of Bird's Eye View (BEV) is essential for ensuring safe and proactive navigation in autonomous driving. Although cooperative percep…