--- _id: '12972' abstract: - lang: eng text: Embroidery is a long-standing and high-quality approach to making logos and images on textiles. Nowadays, it can also be performed via automated machines that weave threads with high spatial accuracy. A characteristic feature of the appearance of the threads is a high degree of anisotropy. The anisotropic behavior is caused by depositing thin but long strings of thread. As a result, the stitched patterns convey both color and direction. Artists leverage this anisotropic behavior to enhance pure color images with textures, illusions of motion, or depth cues. However, designing colorful embroidery patterns with prescribed directionality is a challenging task, one usually requiring an expert designer. In this work, we propose an interactive algorithm that generates machine-fabricable embroidery patterns from multi-chromatic images equipped with user-specified directionality fields.We cast the problem of finding a stitching pattern into vector theory. To find a suitable stitching pattern, we extract sources and sinks from the divergence field of the vector field extracted from the input and use them to trace streamlines. We further optimize the streamlines to guarantee a smooth and connected stitching pattern. The generated patterns approximate the color distribution constrained by the directionality field. To allow for further artistic control, the trade-off between color match and directionality match can be interactively explored via an intuitive slider. We showcase our approach by fabricating several embroidery paths. acknowledgement: This work was supported by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation program (grant agreement No 715767 – MATERIALIZABLE), and FWF Lise Meitner (Grant M 3319). We thank the anonymous reviewers for their insightful feedback; Solal Pirelli, Shardul Chiplunkar, and Paola Mejia for proofreading; everyone in the visual computing group at ISTA for inspiring lunch and coffee breaks; Thibault Tricard for help producing the results of Phasor Noise. article_processing_charge: No article_type: original author: - first_name: Zhenyuan full_name: Liu, Zhenyuan id: 70f0d7cf-ae65-11ec-a14f-89dfc5505b19 last_name: Liu orcid: 0000-0001-9200-5690 - first_name: Michael full_name: Piovarci, Michael id: 62E473F4-5C99-11EA-A40E-AF823DDC885E last_name: Piovarci - first_name: Christian full_name: Hafner, Christian id: 400429CC-F248-11E8-B48F-1D18A9856A87 last_name: Hafner - first_name: Raphael full_name: Charrondiere, Raphael id: a3a24133-2cc7-11ec-be88-8ddaf6f464b1 last_name: Charrondiere - first_name: Bernd full_name: Bickel, Bernd id: 49876194-F248-11E8-B48F-1D18A9856A87 last_name: Bickel orcid: 0000-0001-6511-9385 citation: ama: Liu Z, Piovarci M, Hafner C, Charrondiere R, Bickel B. Directionality-aware design of embroidery patterns. Computer Graphics Forum. 2023;42(2):397-409. doi:10.1111/cgf.14770 apa: 'Liu, Z., Piovarci, M., Hafner, C., Charrondiere, R., & Bickel, B. (2023). Directionality-aware design of embroidery patterns. Computer Graphics Forum. Saarbrucken, Germany: Wiley. https://doi.org/10.1111/cgf.14770 ' chicago: Liu, Zhenyuan, Michael Piovarci, Christian Hafner, Raphael Charrondiere, and Bernd Bickel. “Directionality-Aware Design of Embroidery Patterns.” Computer Graphics Forum. Wiley, 2023. https://doi.org/10.1111/cgf.14770 . ieee: Z. Liu, M. Piovarci, C. Hafner, R. Charrondiere, and B. Bickel, “Directionality-aware design of embroidery patterns,” Computer Graphics Forum, vol. 42, no. 2. Wiley, pp. 397–409, 2023. ista: Liu Z, Piovarci M, Hafner C, Charrondiere R, Bickel B. 2023. Directionality-aware design of embroidery patterns. Computer Graphics Forum. 42(2), 397–409. mla: Liu, Zhenyuan, et al. “Directionality-Aware Design of Embroidery Patterns.” Computer Graphics Forum, vol. 42, no. 2, Wiley, 2023, pp. 397–409, doi:10.1111/cgf.14770 . short: Z. Liu, M. Piovarci, C. Hafner, R. Charrondiere, B. Bickel, Computer Graphics Forum 42 (2023) 397–409. conference: end_date: 2023-05-12 location: Saarbrucken, Germany name: 'EG: Eurographics' start_date: 2023-05-08 date_created: 2023-05-16T08:47:25Z date_published: 2023-05-08T00:00:00Z date_updated: 2023-08-01T14:47:05Z day: '08' ddc: - '004' department: - _id: BeBi doi: '10.1111/cgf.14770 ' ec_funded: 1 external_id: isi: - '001000062600033' file: - access_level: open_access checksum: 4c188c2be4745467a8790bbf5d6491aa content_type: application/pdf creator: mpiovarc date_created: 2023-05-16T08:28:37Z date_updated: 2023-05-16T08:28:37Z file_id: '12974' file_name: Zhenyuan2023.pdf file_size: 24003702 relation: main_file success: 1 file_date_updated: 2023-05-16T08:28:37Z has_accepted_license: '1' intvolume: ' 42' isi: 1 issue: '2' keyword: - embroidery - design - directionality - density - image language: - iso: eng month: '05' oa: 1 oa_version: Published Version page: 397-409 project: - _id: eb901961-77a9-11ec-83b8-f5c883a62027 grant_number: M03319 name: Perception-Aware Appearance Fabrication - _id: 24F9549A-B435-11E9-9278-68D0E5697425 call_identifier: H2020 grant_number: '715767' name: 'MATERIALIZABLE: Intelligent fabrication-oriented Computational Design and Modeling' publication: Computer Graphics Forum publication_identifier: issn: - 1467-8659 publication_status: published publisher: Wiley quality_controlled: '1' status: public title: Directionality-aware design of embroidery patterns tmp: image: /images/cc_by_nc_nd.png legal_code_url: https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode name: Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) short: CC BY-NC-ND (4.0) type: journal_article user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8 volume: 42 year: '2023' ... --- _id: '14241' abstract: - lang: eng text: We present a technique to optimize the reflectivity of a surface while preserving its overall shape. The naïve optimization of the mesh vertices using the gradients of reflectivity simulations results in undesirable distortion. In contrast, our robust formulation optimizes the surface normal as an independent variable that bridges the reflectivity term with differential rendering, and the regularization term with as-rigid-as-possible elastic energy. We further adaptively subdivide the input mesh to improve the convergence. Consequently, our method can minimize the retroreflectivity of a wide range of input shapes, resulting in sharply creased shapes ubiquitous among stealth aircraft and Sci-Fi vehicles. Furthermore, by changing the reward for the direction of the outgoing light directions, our method can be applied to other reflectivity design tasks, such as the optimization of architectural walls to concentrate light in a specific region. We have tested the proposed method using light-transport simulations and real-world 3D-printed objects. acknowledgement: "The authors would like to thank Yuki Koyama and Takeo Igarashi for early discussions, and Yuta Yaguchi for support in 3D printing. This research is partially supported by the Israel Science Foundation grant number 1390/19.\r\n" article_number: '20' article_processing_charge: No author: - first_name: Kenji full_name: Tojo, Kenji last_name: Tojo - first_name: Ariel full_name: Shamir, Ariel last_name: Shamir - first_name: Bernd full_name: Bickel, Bernd id: 49876194-F248-11E8-B48F-1D18A9856A87 last_name: Bickel orcid: 0000-0001-6511-9385 - first_name: Nobuyuki full_name: Umetani, Nobuyuki last_name: Umetani citation: ama: 'Tojo K, Shamir A, Bickel B, Umetani N. Stealth shaper: Reflectivity optimization as surface stylization. In: SIGGRAPH 2023 Conference Proceedings. Association for Computing Machinery; 2023. doi:10.1145/3588432.3591542' apa: 'Tojo, K., Shamir, A., Bickel, B., & Umetani, N. (2023). Stealth shaper: Reflectivity optimization as surface stylization. In SIGGRAPH 2023 Conference Proceedings. Los Angeles, CA, United States: Association for Computing Machinery. https://doi.org/10.1145/3588432.3591542' chicago: 'Tojo, Kenji, Ariel Shamir, Bernd Bickel, and Nobuyuki Umetani. “Stealth Shaper: Reflectivity Optimization as Surface Stylization.” In SIGGRAPH 2023 Conference Proceedings. Association for Computing Machinery, 2023. https://doi.org/10.1145/3588432.3591542.' ieee: 'K. Tojo, A. Shamir, B. Bickel, and N. Umetani, “Stealth shaper: Reflectivity optimization as surface stylization,” in SIGGRAPH 2023 Conference Proceedings, Los Angeles, CA, United States, 2023.' ista: 'Tojo K, Shamir A, Bickel B, Umetani N. 2023. Stealth shaper: Reflectivity optimization as surface stylization. SIGGRAPH 2023 Conference Proceedings. SIGGRAPH: Computer Graphics and Interactive Techniques Conference, 20.' mla: 'Tojo, Kenji, et al. “Stealth Shaper: Reflectivity Optimization as Surface Stylization.” SIGGRAPH 2023 Conference Proceedings, 20, Association for Computing Machinery, 2023, doi:10.1145/3588432.3591542.' short: K. Tojo, A. Shamir, B. Bickel, N. Umetani, in:, SIGGRAPH 2023 Conference Proceedings, Association for Computing Machinery, 2023. conference: end_date: 2023-08-10 location: Los Angeles, CA, United States name: 'SIGGRAPH: Computer Graphics and Interactive Techniques Conference' start_date: 2023-08-06 date_created: 2023-08-27T22:01:17Z date_published: 2023-07-23T00:00:00Z date_updated: 2023-09-05T07:22:03Z day: '23' department: - _id: BeBi doi: 10.1145/3588432.3591542 external_id: arxiv: - '2305.05944' language: - iso: eng main_file_link: - open_access: '1' url: https://doi.org/10.48550/arXiv.2305.05944 month: '07' oa: 1 oa_version: Preprint publication: SIGGRAPH 2023 Conference Proceedings publication_identifier: isbn: - '9798400701597' publication_status: published publisher: Association for Computing Machinery quality_controlled: '1' scopus_import: '1' status: public title: 'Stealth shaper: Reflectivity optimization as surface stylization' type: conference user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 year: '2023' ... --- _id: '14488' abstract: - lang: eng text: 'Portrait viewpoint and illumination editing is an important problem with several applications in VR/AR, movies, and photography. Comprehensive knowledge of geometry and illumination is critical for obtaining photorealistic results. Current methods are unable to explicitly model in 3D while handling both viewpoint and illumination editing from a single image. In this paper, we propose VoRF, a novel approach that can take even a single portrait image as input and relight human heads under novel illuminations that can be viewed from arbitrary viewpoints. VoRF represents a human head as a continuous volumetric field and learns a prior model of human heads using a coordinate-based MLP with individual latent spaces for identity and illumination. The prior model is learned in an auto-decoder manner over a diverse class of head shapes and appearances, allowing VoRF to generalize to novel test identities from a single input image. Additionally, VoRF has a reflectance MLP that uses the intermediate features of the prior model for rendering One-Light-at-A-Time (OLAT) images under novel views. We synthesize novel illuminations by combining these OLAT images with target environment maps. Qualitative and quantitative evaluations demonstrate the effectiveness of VoRF for relighting and novel view synthesis, even when applied to unseen subjects under uncontrolled illumination. This work is an extension of Rao et al. (VoRF: Volumetric Relightable Faces 2022). We provide extensive evaluation and ablative studies of our model and also provide an application, where any face can be relighted using textual input.' acknowledgement: Open Access funding enabled and organized by Projekt DEAL. article_processing_charge: Yes (via OA deal) article_type: original author: - first_name: Pramod full_name: Rao, Pramod last_name: Rao - first_name: B. R. full_name: Mallikarjun, B. R. last_name: Mallikarjun - first_name: Gereon full_name: Fox, Gereon last_name: Fox - first_name: Tim full_name: Weyrich, Tim last_name: Weyrich - first_name: Bernd full_name: Bickel, Bernd id: 49876194-F248-11E8-B48F-1D18A9856A87 last_name: Bickel orcid: 0000-0001-6511-9385 - first_name: Hanspeter full_name: Pfister, Hanspeter last_name: Pfister - first_name: Wojciech full_name: Matusik, Wojciech last_name: Matusik - first_name: Fangneng full_name: Zhan, Fangneng last_name: Zhan - first_name: Ayush full_name: Tewari, Ayush last_name: Tewari - first_name: Christian full_name: Theobalt, Christian last_name: Theobalt - first_name: Mohamed full_name: Elgharib, Mohamed last_name: Elgharib citation: ama: Rao P, Mallikarjun BR, Fox G, et al. A deeper analysis of volumetric relightiable faces. International Journal of Computer Vision. 2023. doi:10.1007/s11263-023-01899-3 apa: Rao, P., Mallikarjun, B. R., Fox, G., Weyrich, T., Bickel, B., Pfister, H., … Elgharib, M. (2023). A deeper analysis of volumetric relightiable faces. International Journal of Computer Vision. Springer Nature. https://doi.org/10.1007/s11263-023-01899-3 chicago: Rao, Pramod, B. R. Mallikarjun, Gereon Fox, Tim Weyrich, Bernd Bickel, Hanspeter Pfister, Wojciech Matusik, et al. “A Deeper Analysis of Volumetric Relightiable Faces.” International Journal of Computer Vision. Springer Nature, 2023. https://doi.org/10.1007/s11263-023-01899-3. ieee: P. Rao et al., “A deeper analysis of volumetric relightiable faces,” International Journal of Computer Vision. Springer Nature, 2023. ista: Rao P, Mallikarjun BR, Fox G, Weyrich T, Bickel B, Pfister H, Matusik W, Zhan F, Tewari A, Theobalt C, Elgharib M. 2023. A deeper analysis of volumetric relightiable faces. International Journal of Computer Vision. mla: Rao, Pramod, et al. “A Deeper Analysis of Volumetric Relightiable Faces.” International Journal of Computer Vision, Springer Nature, 2023, doi:10.1007/s11263-023-01899-3. short: P. Rao, B.R. Mallikarjun, G. Fox, T. Weyrich, B. Bickel, H. Pfister, W. Matusik, F. Zhan, A. Tewari, C. Theobalt, M. Elgharib, International Journal of Computer Vision (2023). date_created: 2023-11-05T23:00:54Z date_published: 2023-10-31T00:00:00Z date_updated: 2023-11-06T08:52:30Z day: '31' department: - _id: BeBi doi: 10.1007/s11263-023-01899-3 language: - iso: eng main_file_link: - open_access: '1' url: https://doi.org/10.1007/s11263-023-01899-3 month: '10' oa: 1 oa_version: Published Version publication: International Journal of Computer Vision publication_identifier: eissn: - 1573-1405 issn: - 0920-5691 publication_status: epub_ahead publisher: Springer Nature quality_controlled: '1' scopus_import: '1' status: public title: A deeper analysis of volumetric relightiable faces type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 year: '2023' ... --- _id: '14628' abstract: - lang: eng text: We introduce a compact, intuitive procedural graph representation for cellular metamaterials, which are small-scale, tileable structures that can be architected to exhibit many useful material properties. Because the structures’ “architectures” vary widely—with elements such as beams, thin shells, and solid bulks—it is difficult to explore them using existing representations. Generic approaches like voxel grids are versatile, but it is cumbersome to represent and edit individual structures; architecture-specific approaches address these issues, but are incompatible with one another. By contrast, our procedural graph succinctly represents the construction process for any structure using a simple skeleton annotated with spatially varying thickness. To express the highly constrained triply periodic minimal surfaces (TPMS) in this manner, we present the first fully automated version of the conjugate surface construction method, which allows novices to create complex TPMS from intuitive input. We demonstrate our representation’s expressiveness, accuracy, and compactness by constructing a wide range of established structures and hundreds of novel structures with diverse architectures and material properties. We also conduct a user study to verify our representation’s ease-of-use and ability to expand engineers’ capacity for exploration. acknowledgement: "The authors thank Mina Konaković Luković and Michael Foshey for their early contributions to this project, David Palmer and Paul Zhang for their insightful discussions about minimal surfaces and the CSCM, Julian Panetta for providing the Elastic Textures code, and Hannes Hergeth for his feedback and support. We also thank our user study participants and anonymous reviewers.\r\nThis material is based upon work supported by the National Science Foundation\r\n(NSF) Graduate Research Fellowship under Grant No. 2141064; the MIT Morningside\r\nAcademy for Design Fellowship; the Defense Advanced Research Projects Agency\r\n(DARPA) Grant No. FA8750-20-C-0075; the ERC Consolidator Grant No. 101045083,\r\n“CoDiNA: Computational Discovery of Numerical Algorithms for Animation and Simulation of Natural Phenomena”; and the NewSat project, which is co-funded by the Operational Program for Competitiveness and Internationalisation (COMPETE2020), Portugal 2020, the European Regional Development Fund (ERDF), and the Portuguese Foundation for Science and Technology (FTC) under the MIT Portugal program." article_number: '168' article_processing_charge: Yes (in subscription journal) article_type: original author: - first_name: Liane full_name: Makatura, Liane last_name: Makatura - first_name: Bohan full_name: Wang, Bohan last_name: Wang - first_name: Yi-Lu full_name: Chen, Yi-Lu id: 0b467602-dbcd-11ea-9d1d-ed480aa46b70 last_name: Chen - first_name: Bolei full_name: Deng, Bolei last_name: Deng - first_name: Christopher J full_name: Wojtan, Christopher J id: 3C61F1D2-F248-11E8-B48F-1D18A9856A87 last_name: Wojtan orcid: 0000-0001-6646-5546 - first_name: Bernd full_name: Bickel, Bernd id: 49876194-F248-11E8-B48F-1D18A9856A87 last_name: Bickel orcid: 0000-0001-6511-9385 - first_name: Wojciech full_name: Matusik, Wojciech last_name: Matusik citation: ama: 'Makatura L, Wang B, Chen Y-L, et al. Procedural metamaterials: A unified procedural graph for metamaterial design. ACM Transactions on Graphics. 2023;42(5). doi:10.1145/3605389' apa: 'Makatura, L., Wang, B., Chen, Y.-L., Deng, B., Wojtan, C., Bickel, B., & Matusik, W. (2023). Procedural metamaterials: A unified procedural graph for metamaterial design. ACM Transactions on Graphics. Association for Computing Machinery. https://doi.org/10.1145/3605389' chicago: 'Makatura, Liane, Bohan Wang, Yi-Lu Chen, Bolei Deng, Chris Wojtan, Bernd Bickel, and Wojciech Matusik. “Procedural Metamaterials: A Unified Procedural Graph for Metamaterial Design.” ACM Transactions on Graphics. Association for Computing Machinery, 2023. https://doi.org/10.1145/3605389.' ieee: 'L. Makatura et al., “Procedural metamaterials: A unified procedural graph for metamaterial design,” ACM Transactions on Graphics, vol. 42, no. 5. Association for Computing Machinery, 2023.' ista: 'Makatura L, Wang B, Chen Y-L, Deng B, Wojtan C, Bickel B, Matusik W. 2023. Procedural metamaterials: A unified procedural graph for metamaterial design. ACM Transactions on Graphics. 42(5), 168.' mla: 'Makatura, Liane, et al. “Procedural Metamaterials: A Unified Procedural Graph for Metamaterial Design.” ACM Transactions on Graphics, vol. 42, no. 5, 168, Association for Computing Machinery, 2023, doi:10.1145/3605389.' short: L. Makatura, B. Wang, Y.-L. Chen, B. Deng, C. Wojtan, B. Bickel, W. Matusik, ACM Transactions on Graphics 42 (2023). date_created: 2023-11-29T15:02:03Z date_published: 2023-10-01T00:00:00Z date_updated: 2023-12-04T08:09:05Z day: '01' ddc: - '531' - '006' department: - _id: GradSch - _id: ChWo - _id: BeBi doi: 10.1145/3605389 file: - access_level: open_access checksum: 0192f597d7a2ceaf89baddfd6190d4c8 content_type: application/zip creator: yichen date_created: 2023-11-29T15:16:01Z date_updated: 2023-11-29T15:16:01Z file_id: '14630' file_name: tog-22-0089-File004.zip file_size: 95467870 relation: main_file success: 1 - access_level: open_access checksum: 7fb024963be81933494f38de191e4710 content_type: application/zip creator: yichen date_created: 2023-11-29T15:16:01Z date_updated: 2023-11-29T15:16:01Z file_id: '14631' file_name: tog-22-0089-File005.zip file_size: 103731880 relation: main_file success: 1 - access_level: open_access checksum: b7d6829ce396e21cac9fae0ec7130a6b content_type: application/pdf creator: dernst date_created: 2023-12-04T08:04:14Z date_updated: 2023-12-04T08:04:14Z file_id: '14638' file_name: 2023_ACMToG_Makatura.pdf file_size: 57067476 relation: main_file success: 1 file_date_updated: 2023-12-04T08:04:14Z has_accepted_license: '1' intvolume: ' 42' issue: '5' keyword: - Computer Graphics and Computer-Aided Design language: - iso: eng month: '10' oa: 1 oa_version: Published Version project: - _id: 34bc2376-11ca-11ed-8bc3-9a3b3961a088 grant_number: '101045083' name: Computational Discovery of Numerical Algorithms for Animation and Simulation of Natural Phenomena publication: ACM Transactions on Graphics publication_identifier: issn: - 0730-0301 - 1557-7368 publication_status: published publisher: Association for Computing Machinery quality_controlled: '1' status: public title: 'Procedural metamaterials: A unified procedural graph for metamaterial design' type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 42 year: '2023' ... --- _id: '12976' abstract: - lang: eng text: "3D printing based on continuous deposition of materials, such as filament-based 3D printing, has seen widespread adoption thanks to its versatility in working with a wide range of materials. An important shortcoming of this type of technology is its limited multi-material capabilities. While there are simple hardware designs that enable multi-material printing in principle, the required software is heavily underdeveloped. A typical hardware design fuses together individual materials fed into a single chamber from multiple inlets before they are deposited. This design, however, introduces a time delay between the intended material mixture and its actual deposition. In this work, inspired by diverse path planning research in robotics, we show that this mechanical challenge can be addressed via improved printer control. We propose to formulate the search for optimal multi-material printing policies in a reinforcement\r\nlearning setup. We put forward a simple numerical deposition model that takes into account the non-linear material mixing and delayed material deposition. To validate our system we focus on color fabrication, a problem known for its strict requirements for varying material mixtures at a high spatial frequency. We demonstrate that our learned control policy outperforms state-of-the-art hand-crafted algorithms." acknowledgement: This work is graciously supported by FWF Lise Meitner (Grant M 3319). Kang Liao sincerely thank Emiliano Luci, Chunyu Lin, and Yao Zhao for their huge support. article_processing_charge: No author: - first_name: Kang full_name: Liao, Kang last_name: Liao - first_name: Thibault full_name: Tricard, Thibault last_name: Tricard - first_name: Michael full_name: Piovarci, Michael id: 62E473F4-5C99-11EA-A40E-AF823DDC885E last_name: Piovarci orcid: 0000-0002-5062-4474 - first_name: Hans-Peter full_name: Seidel, Hans-Peter last_name: Seidel - first_name: Vahid full_name: Babaei, Vahid last_name: Babaei citation: ama: 'Liao K, Tricard T, Piovarci M, Seidel H-P, Babaei V. Learning deposition policies for fused multi-material 3D printing. In: 2023 IEEE International Conference on Robotics and Automation. Vol 2023. IEEE; 2023:12345-12352. doi:10.1109/ICRA48891.2023.10160465' apa: 'Liao, K., Tricard, T., Piovarci, M., Seidel, H.-P., & Babaei, V. (2023). Learning deposition policies for fused multi-material 3D printing. In 2023 IEEE International Conference on Robotics and Automation (Vol. 2023, pp. 12345–12352). London, United Kingdom: IEEE. https://doi.org/10.1109/ICRA48891.2023.10160465' chicago: Liao, Kang, Thibault Tricard, Michael Piovarci, Hans-Peter Seidel, and Vahid Babaei. “Learning Deposition Policies for Fused Multi-Material 3D Printing.” In 2023 IEEE International Conference on Robotics and Automation, 2023:12345–52. IEEE, 2023. https://doi.org/10.1109/ICRA48891.2023.10160465. ieee: K. Liao, T. Tricard, M. Piovarci, H.-P. Seidel, and V. Babaei, “Learning deposition policies for fused multi-material 3D printing,” in 2023 IEEE International Conference on Robotics and Automation, London, United Kingdom, 2023, vol. 2023, pp. 12345–12352. ista: 'Liao K, Tricard T, Piovarci M, Seidel H-P, Babaei V. 2023. Learning deposition policies for fused multi-material 3D printing. 2023 IEEE International Conference on Robotics and Automation. ICRA: International Conference on Robotics and Automation vol. 2023, 12345–12352.' mla: Liao, Kang, et al. “Learning Deposition Policies for Fused Multi-Material 3D Printing.” 2023 IEEE International Conference on Robotics and Automation, vol. 2023, IEEE, 2023, pp. 12345–52, doi:10.1109/ICRA48891.2023.10160465. short: K. Liao, T. Tricard, M. Piovarci, H.-P. Seidel, V. Babaei, in:, 2023 IEEE International Conference on Robotics and Automation, IEEE, 2023, pp. 12345–12352. conference: end_date: 2023-06-02 location: London, United Kingdom name: 'ICRA: International Conference on Robotics and Automation' start_date: 2023-05-29 date_created: 2023-05-16T09:14:09Z date_published: 2023-07-04T00:00:00Z date_updated: 2023-12-13T11:20:00Z day: '04' ddc: - '004' department: - _id: BeBi doi: 10.1109/ICRA48891.2023.10160465 external_id: isi: - '001048371104068' file: - access_level: open_access checksum: daeaa67124777d88487f933ea3f77164 content_type: application/pdf creator: mpiovarc date_created: 2023-05-16T09:12:05Z date_updated: 2023-05-16T09:12:05Z file_id: '12977' file_name: Liao2023.pdf file_size: 5367986 relation: main_file success: 1 file_date_updated: 2023-05-16T09:12:05Z has_accepted_license: '1' intvolume: ' 2023' isi: 1 keyword: - reinforcement learning - deposition - control - color - multi-filament language: - iso: eng month: '07' oa: 1 oa_version: Submitted Version page: 12345-12352 project: - _id: eb901961-77a9-11ec-83b8-f5c883a62027 grant_number: M03319 name: Perception-Aware Appearance Fabrication publication: 2023 IEEE International Conference on Robotics and Automation publication_identifier: eisbn: - '9798350323658' issn: - 1050-4729 publication_status: published publisher: IEEE quality_controlled: '1' scopus_import: '1' status: public title: Learning deposition policies for fused multi-material 3D printing type: conference user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 2023 year: '2023' ...