Search Results for author:
Found 4 papers, 2 papers with code
Are NeRFs ready for autonomous driving? Towards closing the real-to-simulation gap
Specifically, we evaluate object detectors and an online mapping model on real and simulated data, and study the effects of different fine-tuning strategies. Our results show notable improvements in model robustness to simulated data, even improving real-world performance in some cases.
Poisson Multi-Bernoulli Mapping Using Gibbs Sampling
The proposed method can handle uncertainties in the data associations and the cardinality of the set of landmarks, and is parallelizable, making it suitable for large-scale problems.
Poisson Multi-Bernoulli Approximations for Multiple Extended Object Filtering
The Poisson multi-Bernoulli mixture (PMBM) is a multi-object conjugate prior for the closed-form Bayes random finite sets filter.
Poisson multi-Bernoulli conjugate prior for multiple extended object filtering
Both the prediction and the update preserve the PMBM form of the density, and in this sense the PMBM density is a conjugate prior.
