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Found 13 papers, 9 papers with code
Connecting Look and Feel: Associating the visual and tactile properties of physical materials
A thin flexible fabric, when draped, tends to look different from a heavy stiff fabric.
The Feeling of Success: Does Touch Sensing Help Predict Grasp Outcomes?
In this work, we investigate the question of whether touch sensing aids in predicting grasp outcomes within a multimodal sensing framework that combines vision and touch.
ViTac: Feature Sharing between Vision and Tactile Sensing for Cloth Texture Recognition
In this paper, addressing for the first time (to the best of our knowledge) texture recognition from tactile images and vision, we propose a new fusion method named Deep Maximum Covariance Analysis (DMCA) to learn a joint latent space for sharing features through vision and tactile sensing.
More Than a Feeling: Learning to Grasp and Regrasp using Vision and Touch
This model -- a deep, multimodal convolutional network -- predicts the outcome of a candidate grasp adjustment, and then executes a grasp by iteratively selecting the most promising actions.
3D Shape Perception from Monocular Vision, Touch, and Shape Priors
Perceiving accurate 3D object shape is important for robots to interact with the physical world.
Real-time Soft Body 3D Proprioception via Deep Vision-based Sensing
Soft bodies made from flexible and deformable materials are popular in many robotics applications, but their proprioceptive sensing has been a long-standing challenge.
Robotics
Learning an Action-Conditional Model for Haptic Texture Generation
Therefore, it is challenging to model the mapping from material and user interactions to haptic feedback in a way that generalizes over many variations of the user's input.
Learning Hierarchical Control for Robust In-Hand Manipulation
Finally, we show how our approach generalizes to objects of other shapes.
Simulation of Vision-based Tactile Sensors using Physics based Rendering
Tactile sensing has seen a rapid adoption with the advent of vision-based tactile sensors.
Robotics Graphics
ObjectFolder 2.0: A Multisensory Object Dataset for Sim2Real Transfer
We present ObjectFolder 2. 0, a large-scale, multisensory dataset of common household objects in the form of implicit neural representations that significantly enhances ObjectFolder 1. 0 in three aspects.
PoseIt: A Visual-Tactile Dataset of Holding Poses for Grasp Stability Analysis
To facilitate the study of how holding poses affect grasp stability, we present PoseIt, a novel multi-modal dataset that contains visual and tactile data collected from a full cycle of grasping an object, re-positioning the arm to one of the sampled poses, and shaking the object.
Touch and Go: Learning from Human-Collected Vision and Touch
The ability to associate touch with sight is essential for tasks that require physically interacting with objects in the world.
Controllable Visual-Tactile Synthesis
Deep generative models have various content creation applications such as graphic design, e-commerce, and virtual Try-on.
