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Found 8 papers, 4 papers with code
Dynamic High Resolution Deformable Articulated Tracking
The last several years have seen significant progress in using depth cameras for tracking articulated objects such as human bodies, hands, and robotic manipulators.
CHALET: Cornell House Agent Learning Environment
We present CHALET, a 3D house simulator with support for navigation and manipulation.
Early Fusion for Goal Directed Robotic Vision
Building perceptual systems for robotics which perform well under tight computational budgets requires novel architectures which rethink the traditional computer vision pipeline.
Part Segmentation for Highly Accurate Deformable Tracking in Occlusions via Fully Convolutional Neural Networks
While recent work has shown direct estimation techniques can be quite powerful, geometric tracking methods using point clouds can provide a very high level of 3D accuracy which is necessary for many robotic applications.
FLUID: A Unified Evaluation Framework for Flexible Sequential Data
To foster research towards the goal of general ML methods, we introduce a new unified evaluation framework - FLUID (Flexible Sequential Data).
Amodal 3D Reconstruction for Robotic Manipulation via Stability and Connectivity
By using these priors over the physical properties of objects, our system improves reconstruction quality not just by standard visual metrics, but also performance of model-based control on a variety of robotics manipulation tasks in challenging, cluttered environments.
Break and Make: Interactive Structural Understanding Using LEGO Bricks
We pair this simulator with a new dataset of fan-made LEGO creations that have been uploaded to the internet in order to provide complex scenes containing over a thousand unique brick shapes.
ENTL: Embodied Navigation Trajectory Learner
ENTL's generic architecture enables sharing of the spatio-temporal sequence encoder for multiple challenging embodied tasks.
