most citedTable-Top Scene Analysis Using Knowledge-Supervised MCMC

2 citations · 3 across the 7 of their papers we have counts for

collaborators

8 papers

cs.RO2021

Road Mapping and Localization using Sparse Semantic Visual Features

Wentao Cheng, Sheng Yang, Maomin Zhou +3

We present a novel method for visual mapping and localization for autonomous vehicles, by extracting, modeling, and optimizing semantic road elements. Specifically, our method inte…

cs.RO2021

OCRTOC: A Cloud-Based Competition and Benchmark for Robotic Grasping and Manipulation

Ziyuan Liu, Wei Liu, Yuzhe Qin +8

In this paper, we propose a cloud-based benchmark for robotic grasping and manipulation, called the OCRTOC benchmark. The benchmark focuses on the object rearrangement problem, spe…

cs.CV2020

Online Semantic Exploration of Indoor Maps

Ziyuan Liu, Dong Chen, Georg von Wichert

In this paper we propose a method to extract an abstracted floor plan from typical grid maps using Bayesian reasoning. The result of this procedure is a probabilistic generative mo…

cs.CV2020

Applying Rule-Based Context Knowledge to Build Abstract Semantic Maps of Indoor Environments

Ziyuan Liu, Georg von Wichert

In this paper, we propose a generalizable method that systematically combines data driven MCMC samplingand inference using rule-based context knowledge for data abstraction. In par…

cs.CV2020

Particle Filter Based Monocular Human Tracking with a 3D Cardbox Model and a Novel Deterministic Resampling Strategy

Ziyuan Liu, Dongheui Lee, Wolfgang Sepp

The challenge of markerless human motion tracking is the high dimensionality of the search space. Thus, efficient exploration in the search space is of great significance. In this…

cs.CV20202 cited

Table-Top Scene Analysis Using Knowledge-Supervised MCMC

Ziyuan Liu, Dong Chen, Kai M. Wurm +1

In this paper, we propose a probabilistic method to generate abstract scene graphs for table-top scenes from 6D object pose estimates. We explicitly make use of task-specfic contex…