VoluMon is a novel approach to enable a deep neural network to predict the size and pose of objects without requiring 3D annotations or mesh models.

[pdf], [video]

Robust Object-Based SLAM for High-Speed Autonomous Navigation (ROSHAN) improves object-level SLAM with ellipsoid landmarks for autonomous navigation by incorporating texture and semantic measurements.

[pdf]

We enable more efficient navigation by training a neural network to predict a sampling distribution from object-level maps and occupancy maps.

[pdf][video]

Deep Inference for Covariance Estimation (DICE) uses a deep convolutional neural network to predict noise models for high dimensional, complex sensors.

[pdf][video]