16 citations · 27 across the 5 of their papers we have counts for
10 papers
Semantic keypoint-based pose estimation from single RGB frames
Karl Schmeckpeper, Philip R. Osteen, Yufu Wang +6
This paper presents an approach to estimating the continuous 6-DoF pose of an object from a single RGB image. The approach combines semantic keypoints predicted by a convolutional…
Cross-modal Map Learning for Vision and Language Navigation
Georgios Georgakis, Karl Schmeckpeper, Karan Wanchoo +4
We consider the problem of Vision-and-Language Navigation (VLN). The majority of current methods for VLN are trained end-to-end using either unstructured memory such as LSTM, or us…
Uncertainty-driven Planner for Exploration and Navigation
Georgios Georgakis, Bernadette Bucher, Anton Arapin +3
We consider the problems of exploration and point-goal navigation in previously unseen environments, where the spatial complexity of indoor scenes and partial observability constit…
Bridge Data: Boosting Generalization of Robotic Skills with Cross-Domain Datasets
Frederik Ebert, Yanlai Yang, Karl Schmeckpeper +5
Robot learning holds the promise of learning policies that generalize broadly. However, such generalization requires sufficiently diverse datasets of the task of interest, which ca…
Object-centric Video Prediction without Annotation
Karl Schmeckpeper, Georgios Georgakis, Kostas Daniilidis
In order to interact with the world, agents must be able to predict the results of the world's dynamics. A natural approach to learn about these dynamics is through video predictio…
Deformable Linear Object Prediction Using Locally Linear Latent Dynamics
Wenbo Zhang, Karl Schmeckpeper, Pratik Chaudhari +1
We propose a framework for deformable linear object prediction. Prediction of deformable objects (e.g., rope) is challenging due to their non-linear dynamics and infinite-dimension…