ELLIPSDF: Joint Object Pose and Shape Optimization with a Bi-level Ellipsoid and Signed Distance Function Description

08/01/2021
by   Mo Shan, et al.
0

Autonomous systems need to understand the semantics and geometry of their surroundings in order to comprehend and safely execute object-level task specifications. This paper proposes an expressive yet compact model for joint object pose and shape optimization, and an associated optimization algorithm to infer an object-level map from multi-view RGB-D camera observations. The model is expressive because it captures the identities, positions, orientations, and shapes of objects in the environment. It is compact because it relies on a low-dimensional latent representation of implicit object shape, allowing onboard storage of large multi-category object maps. Different from other works that rely on a single object representation format, our approach has a bi-level object model that captures both the coarse level scale as well as the fine level shape details. Our approach is evaluated on the large-scale real-world ScanNet dataset and compared against state-of-the-art methods.

READ FULL TEXT

page 4

page 7

page 11

page 12

page 13

research
05/11/2020

FroDO: From Detections to 3D Objects

Object-oriented maps are important for scene understanding since they jo...
research
12/14/2021

OMAD: Object Model with Articulated Deformations for Pose Estimation and Retrieval

Articulated objects are pervasive in daily life. However, due to the int...
research
12/31/2021

iCaps: Iterative Category-level Object Pose and Shape Estimation

This paper proposes a category-level 6D object pose and shape estimation...
research
11/28/2022

In-Hand 3D Object Scanning from an RGB Sequence

We propose a method for in-hand 3D scanning of an unknown object from a ...
research
08/11/2020

GeLaTO: Generative Latent Textured Objects

Accurate modeling of 3D objects exhibiting transparency, reflections and...
research
08/09/2022

Learning to Complete Object Shapes for Object-level Mapping in Dynamic Scenes

In this paper, we propose a novel object-level mapping system that can s...
research
08/16/2019

Hyperparameter-Free Losses for Model-Based Monocular Reconstruction

This work proposes novel hyperparameter-free losses for single view 3D r...

Please sign up or login with your details

Forgot password? Click here to reset