A dataset is crucial for model learning and evaluation. Choosing the right dataset to use or making a new dataset requires the knowledge of those that are available. In this work, we provide that knowledge, by reviewing twenty datasets that were published in the recent six years and that are directly related to object manipulation. We report on modalities, activities, and annotations for each individual dataset and give our view on its use for object manipulation. We also compare the datasets and summarize them. We conclude with our suggestion on future datasets
Learning object models in the wild from natural human interactions is an essential ability for robot...
The motivation behind our work is to review and analyze the most relevant studies on deep reinforcem...
The experiment dataset files are the result of 4 different experiments on the influence of the rewar...
A dataset is crucial for model learning and evaluation. Choosing the right dataset to use or making ...
Data sets are crucial not only for model learning and evaluation but also to advance knowledge on hu...
Abstract. Appropriate datasets are required at all stages of object recognition research, including ...
This dataset consists of nine object manipulation actions performed by 12 humans: pick and place, pu...
This paper reports the activities and outcomes in the Workshop on Grasping and Manipulation Datasets...
Abstract — In this paper we present the Yale-CMU-Berkeley (YCB) Object and Model set, intended to be...
<p>Improving robotic manipulation is critical for robots to be actively useful in realworld factorie...
In visual object recognition, it is important to understand which object properties are important fo...
We review the work on data-driven grasp synthesis and the methodologies for sampling and ranking can...
This paper offers an account of data manipulation in scientific experiments. It will be shown that i...
This publication is with permission of the rights owner freely accessible due to an Alliance licence...
Learning object models in the wild from natural human interactions is an essential ability for robot...
Learning object models in the wild from natural human interactions is an essential ability for robot...
The motivation behind our work is to review and analyze the most relevant studies on deep reinforcem...
The experiment dataset files are the result of 4 different experiments on the influence of the rewar...
A dataset is crucial for model learning and evaluation. Choosing the right dataset to use or making ...
Data sets are crucial not only for model learning and evaluation but also to advance knowledge on hu...
Abstract. Appropriate datasets are required at all stages of object recognition research, including ...
This dataset consists of nine object manipulation actions performed by 12 humans: pick and place, pu...
This paper reports the activities and outcomes in the Workshop on Grasping and Manipulation Datasets...
Abstract — In this paper we present the Yale-CMU-Berkeley (YCB) Object and Model set, intended to be...
<p>Improving robotic manipulation is critical for robots to be actively useful in realworld factorie...
In visual object recognition, it is important to understand which object properties are important fo...
We review the work on data-driven grasp synthesis and the methodologies for sampling and ranking can...
This paper offers an account of data manipulation in scientific experiments. It will be shown that i...
This publication is with permission of the rights owner freely accessible due to an Alliance licence...
Learning object models in the wild from natural human interactions is an essential ability for robot...
Learning object models in the wild from natural human interactions is an essential ability for robot...
The motivation behind our work is to review and analyze the most relevant studies on deep reinforcem...
The experiment dataset files are the result of 4 different experiments on the influence of the rewar...