Search Results for author:
Found 9 papers, 5 papers with code
Compositional Semantics for Open Vocabulary Spatio-semantic Representations
General-purpose mobile robots need to complete tasks without exact human instructions.
R-Cut: Enhancing Explainability in Vision Transformers with Relationship Weighted Out and Cut
Our method aims to improve trust in classification results and empower users to gain a deeper understanding of the model for downstream tasks by providing visualizations of class-specific maps.
Learning to Predict Navigational Patterns from Partial Observations
We demonstrate how to infer global navigational patterns by fitting a maximum likelihood graph to the DSLP field.
Ranked #1 on
Lane Detection
on nuScenes
Predictive World Models from Real-World Partial Observations
By extending HVAEs to cases where complete ground truth states do not exist, we facilitate continual learning of spatial prediction as a step towards realizing explainable and comprehensive predictive world models for real-world mobile robotics applications.
ViCE: Improving Dense Representation Learning by Superpixelization and Contrasting Cluster Assignment
Recent self-supervised models have demonstrated equal or better performance than supervised methods, opening for AI systems to learn visual representations from practically unlimited data.
Learning a Model for Inferring a Spatial Road Lane Network Graph using Self-Supervision
A formal road lane network model is presented and proves that any structured road scene can be represented by a directed acyclic graph of at most depth three while retaining the notion of intersection regions, and that this is the most compressed representation.
Probabilistic Rainfall Estimation from Automotive Lidar
Prior work has established that rainfall rate is a useful measure for the adversity of atmospheric weather conditions.
Thermalization in Large-N CFTs
In d-dimensional CFTs with a large number of degrees of freedom an important set of operators consists of the stress tensor and its products, multi stress tensors.
High Energy Physics - Theory
Learning a Directional Soft Lane Affordance Model for Road Scenes Using Self-Supervision
Humans navigate complex environments in an organized yet flexible manner, adapting to the context and implicit social rules.
