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Found 7 papers, 3 papers with code
ASDF: Assembly State Detection Utilizing Late Fusion by Integrating 6D Pose Estimation
Existing work, combining object detection/6D pose estimation and assembly state detection focuses either on pure deep learning-based approaches, or limit the assembly state detection to building blocks.
GBOT: Graph-Based 3D Object Tracking for Augmented Reality-Assisted Assembly Guidance
Augmented reality assembly guidance requires 6D object poses of target objects in real time.
DynaMoN: Motion-Aware Fast and Robust Camera Localization for Dynamic Neural Radiance Fields
The accurate reconstruction of dynamic scenes with neural radiance fields is significantly dependent on the estimation of camera poses.
NeRFtrinsic Four: An End-To-End Trainable NeRF Jointly Optimizing Diverse Intrinsic and Extrinsic Camera Parameters
Current research on the joint optimization of camera parameters and NeRF focuses on refining noisy extrinsic camera parameters and often relies on the preprocessing of intrinsic camera parameters.
HouseCat6D -- A Large-Scale Multi-Modal Category Level 6D Object Perception Dataset with Household Objects in Realistic Scenarios
Estimating 6D object poses is a major challenge in 3D computer vision.
Multilevel Monte Carlo learning
The idea is to train several neural networks, each having a certain approximation quality and computational complexity, with training data computed from so-called level estimators, introduced by Giles.
Numerical Analysis Numerical Analysis
Improving Sentiment Analysis with Biofeedback Data
Humans frequently are able to read and interpret emotions of others by directly taking verbal and non-verbal signals in human-to-human communication into account or to infer or even experience emotions from mediated stories.
