Human-to-Robot Handovers of Unseen Containers with Unknown Filling
System for human-to-robot handover of unseen containers with unknown filling, with perception (vision) and robot control modules.
System for human-to-robot handover of unseen containers with unknown filling, with perception (vision) and robot control modules.
Real-to-simulation framework for safe human-to-robot handovers using visual estimation of object and hand properties.
Joint localisation and dimension estimation of container-like objects using generative 3D sampling and multi-view fitting.
Generic whole-body control library implementing inverse dynamics and kinematics using quadratic programming.
Dynamical systems model that classifies handovers as careful or not based on motion patterns.
Models for identifying actions (shaking or pouring) and classifying content type and level using audio spectrograms.
Plug‑and‑play augmentation scheme using max‑entropy transformations to improve robustness to common corruptions.
Reproduce the results of NADs, capturing directional inductive biases of neural architectures.
Reproduce the analysis of discriminative features and their influence on deep network decision boundaries.
Generate adversarial images by perturbing semantic regions within natural color ranges.
Toolkit for the CORSMAL Challenge, providing metrics and scripts for benchmarking submissions and evaluation.
Toolkit with utilities for the CORSMAL Hand-Occluded Containers (CHOC) dataset, including loading, visualization, and evaluation tools.
Toolkit to automatically render composite images of handheld containers over real backgrounds using Blender and Python, combining synthetic objects, hands, and forearms.
Software to run a multi-branch convolutional neural network, adapted from NOCS and retrained at QMUL, for category-level 6D pose estimation on images of hand-occluded containers.
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Improving Generalization of Deep Networks for Estimating Physical Properties of
Containers and Fillings Software of the solution submitted by the team Squids at the 2022 ICASSP CORSMAL challenge. [code] [paper] |
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Shared Transformer Encoder with Mask-based 3D Model Estimation for Container Mass
Estimation Software of the solution submitted by the team KEIO-ICS at the 2022 ICASSP CORSMAL challenge. [code] |
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Container localisation and mass estimation with an RGB-D camera Software of the solution submitted by the team Visual at the 2022 ICASSP CORSMAL challenge. [code] [paper] |
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Filling mass estimation using multi-modal observations of human-robot
handovers Software of the solution submitted by the Because It's Tactile team at the 2020 CORSMAL challenge. [code] [paper] [video] [slides] |
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Audio-Visual Hybrid Approach for Filling Mass Estimation Software of the solution submitted by the HVRL team at the 2020 CORSMAL challenge. [code] [paper] [video] [slides] |
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NTNU-ERC solution for filling mass estimation Software of the solution submitted by the NTNU-ERC team at the 2020 CORSMAL challenge. [code] [slides] |