1 citations · 1 across the 3 of their papers we have counts for
5 papers
AnyThermal: Towards Learning Universal Representations for Thermal Perception
Parv Maheshwari, Jay Karhade, Yogesh Chawla +8
We present AnyThermal, a thermal backbone that captures robust task-agnostic thermal features suitable for a variety of tasks such as cross-modal place recognition, thermal segment…
BETTY Dataset: A Multi-modal Dataset for Full-Stack Autonomy
Micah Nye, Ayoub Raji, Andrew Saba +9
We present the BETTY dataset, a large-scale, multi-modal dataset collected on several autonomous racing vehicles, targeting supervised and self-supervised state estimation, dynamic…
TartanGround: A Large-Scale Dataset for Ground Robot Perception and Navigation
Manthan Patel, Fan Yang, Yuheng Qiu +4
We present TartanGround, a large-scale, multi-modal dataset to advance the perception and autonomy of ground robots operating in diverse environments. This dataset, collected in va…
SALON: Self-supervised Adaptive Learning for Off-road Navigation
Matthew Sivaprakasam, Samuel Triest, Cherie Ho +5
Autonomous robot navigation in off-road environments presents a number of challenges due to its lack of structure, making it difficult to handcraft robust heuristics for diverse sc…
LogiCity: Advancing Neuro-Symbolic AI with Abstract Urban Simulation
Bowen Li, Zhaoyu Li, Qiwei Du +10
Recent years have witnessed the rapid development of Neuro-Symbolic (NeSy) AI systems, which integrate symbolic reasoning into deep neural networks. However, most of the existing b…