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   Lu, Shiyang ; Chang, Haonan ; Pu_Jing, Eric ; Boularias, Abdeslam ; Bekris, Kostas ( November 2023 , Proceedings of the 2023 Conference on Robot Learning (CORL))

   This work presents OVIR-3D, a straightforward yet effective method for open-vocabulary 3D object instance retrieval without using any 3D data for training. Given a language query, the proposed method is able to return a ranked set of 3D object instance segments based on the feature similarity of the instance and the text query. This is achieved by a multi-view fusion of text-aligned 2D region proposals into 3D space, where the 2D region proposal network could leverage 2D datasets, which are more accessible and typically larger than 3D datasets. The proposed fusion process is efficient as it can be performed in real-time for most indoor 3D scenes and does not require additional training in 3D space. Experiments on public datasets and a real robot show the effectiveness of the method and its potential for applications in robot navigation and manipulation. 

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2. MAKER: 3D Pen Utilization in 3D Printing Practices

   Imeri, Astrit ; Russell, Nicholas ; Rust, James ; Sahin, Serhat ; Fidan, Ismail ( June 2017 , 2017 ASEE Annual Conference Proceedings)

   During the 2017 Engineering-a-Future activities at Tennessee Tech University, a set of 3D Pen activities has been organized for the female Middle School Students (5th and 6th grades) so that they learn more about the engineering fields and their practices in daily life. Various Additive Manufacturing technologies have been presented to students, and students have toured the lab facilities. During the 45-minute timeframe, students were grouped and constructed 3D art objects (butterfly, necklace, bird, and glasses) using the available 3D Pens. It was observed that the students had high enthusiasm about the new technology. This study will present the utilization of 3D Printing Pens in various practices, and report the current advantageous and disadvantageous of 3D Pen exercises detected through recent studies. 

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3. 3d modularity

   https://doi.org/10.1007/JHEP10(2019)010  

   Cheng, Miranda C.N. ; Chun, Sungbong ; Ferrari, Francesca ; Gukov, Sergei ; Harrison, Sarah M. ( October 2019 , Journal of High Energy Physics)
4. 3D metamaterials

   https://doi.org/10.1038/s42254-018-0018-y  

   Kadic, Muamer ; Milton, Graeme W. ; van Hecke, Martin ; Wegener, Martin ( March 2019 , Nature Reviews Physics)
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