Search Results for author:
Found 3 papers, 1 papers with code
Learning Spatial Common Sense with Geometry-Aware Recurrent Networks
The proposed networks learn to "lift" and integrate 2D visual features over time into latent 3D feature maps of the scene.
Reinforcement Learning of Active Vision for Manipulating Objects under Occlusions
We propose hand/eye con-trollers that learn to move the camera to keep the object within the field of viewand visible, in coordination to manipulating it to achieve the desired goal, e. g., pushing it to a target location.
Geometry-Aware Recurrent Neural Networks for Active Visual Recognition
We present recurrent geometry-aware neural networks that integrate visual information across multiple views of a scene into 3D latent feature tensors, while maintaining an one-to-one mapping between 3D physical locations in the world scene and latent feature locations.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
