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Current methods for 3D object reconstruction from a set of planar cross-sections still struggle to capture detailed topology or require a considerable number of cross-sections.
Learning to paint with model-based deep reinforcement learning
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Superquadrics revisited: Learning 3d shape parsing beyond cuboids
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Unsupervised doodling and painting with improved SPIRAL
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W. E. Lorensen and H. E. Cline · 1987
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Shape reconstruction from planar cross sections
J.-D. Boissonnat · 1988
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A combined corner and edge detector
C. Harris, M. Stephens, et al · 1988
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A 3d reconstruction of vascular structures from two x-ray angiograms using an adapted simulated annealing algorithm
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Good features to track
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Arbitrary topology shape reconstruction from planar cross sections
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Susan—a new approach to low level image processing
S. M. Smith and J. M. Brady · 1997
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Robust image corner detection through curvature scale space
F. Mokhtarian and R. Suomela · 1998
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M. Trajković and M. Hedley · 1998
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3d reconstruction from two orthogonal views using simulated annealing approach
J. Ning, S. McClean, and K. Cranley · 2001
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Smooth shape-based interpolation using the conjugate gradient method
B. Csébfalvi, L. Neumann, A. Kanitsar, and M. E. Gröller · 2002
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Modeling 3d shapes by reinforcement learning
C. Lin, T. Fan, W. Wang, and M. Nießner · 2003
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Simplification and repair of polygonal models using volumetric techniques
F. S. Nooruddin and G. Turk · 2003
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Distinctive image features from scale-invariant keypoints
D. G. Lowe · 2004
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Shape transformation using variational implicit functions
G. Turk and J. F. O’brien · 2005
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Poisson Surface Reconstruction
M. Kazhdan, M. Bolitho, and H. Hoppe · 2006
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A generic software design for delaunay refinement meshing
L. Rineau and M. Yvinec · 2006
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Machine learning for high-speed corner detection
E. Rosten and T. Drummond · 2006
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Competing fronts for coarse–to–fine surface reconstruction
A. Sharf, T. Lewiner, A. Shamir, L. Kobbelt, and D. Cohen-Or · 2006
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Editing the topology of 3d models by sketching
T. Ju, Q.-Y. Zhou, and S.-M. Hu · 2007
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Template-based surface reconstruction from cross-sections
M. Holloway, C. Grimm, and T. Ju · 2016
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Continuous control with deep reinforcement learning
T. P. Lillicrap, J. J. Hunt, A. Pritzel, N. Heess, T. Erez, Y. Tassa, D. Silver, and D. Wierstra · 2016
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Topology-controlled reconstruction of multi-labelled domains from cross-sections
Z. Huang, M. Zou, N. Carr, and T. Ju · 2017
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Overcoming exploration in reinforcement learning with demonstrations
A. Nair, B. McGrew, M. Andrychowicz, W. Zaremba, and P. Abbeel · 2017
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Csgnet: Neural shape parser for constructive solid geometry
G. Sharma, R. Goyal, D. Liu, E. Kalogerakis, and S. Maji · 2017
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L. Liu, C. Bajaj, J. O. Deasy, D. A. Low, and T. Ju · 2008
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Surface reconstruction via geodesic interpolation
N. Sprynski, N. Szafran, B. Lacolle, and L. Biard · 2008
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No-regret reductions for imitation learning and structured prediction
S. Ross, G. J. Gordon, and J. A. Bagnell · 2010
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Online reconstruction of 3d objects from arbitrary cross-sections
A. Bermano, A. Vaxman, and C. Gotsman · 2011
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Shape grammar parsing via reinforcement learning
O. Teboul, I. Kokkinos, L. Simon, P. Koutsourakis, and N. Paragios · 2011
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Polygon mesh repairing: An application perspective
M. Attene, M. Campen, and L. Kobbelt · 2013
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Learning shape abstractions by assembling volumetric primitives
S. Tulsiani, H. Su, L. J. Guibas, A. A. Efros, and J. Malik · 2017
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Leveraging demonstrations for deep reinforcement learning on robotics problems with sparse rewards
M. Vecerík, T. Hester, J. Scholz, F. Wang, O. Pietquin, B. Piot, N. Heess, T. Rothörl, T. Lampe, and M. A. Riedmiller · 2017
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Synthesizing programs for images using reinforced adversarial learning
Y. Ganin, T. Kulkarni, I. Babuschkin, S. M. A. Eslami, and O. Vinyals · 2018
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An intriguing failing of convolutional neural networks and the coordconv solution
R. Liu, J. Lehman, P. Molino, F. P. Such, E. Frank, A. Sergeev, and J. Yosinski · 2018
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Learning deep sketch abstraction
U. R. Muhammad, Y. Yang, Y. Song, T. Xiang, and T. M. Hospedales · 2018
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Pretraining deep actor-critic reinforcement learning algorithms with expert demonstrations
X. Zhang and H. Ma · 2018
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Learning to sketch with deep Q networks and demonstrated strokes
T. Zhou, C. Fang, Z. Wang, J. Yang, B. Kim, Z. Chen, J. Brandt, and D. Terzopoulos · 2018
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3d shape reconstruction from images in the frequency domain
W. Shen, Y. Jia, and Y. Wu · 2019
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Connect-and-Slice: an hybrid approach for reconstructing 3D objects
H. Fang and F. Lafarge · 2020
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Reagent: Point cloud registration using imitation and reinforcement learning
D. Bauer, T. Patten, and M. Vincze · 2021
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Biventricular surface reconstruction from cine mri contours using point completion networks
M. Beetz, A. Banerjee, and V. Grau · 2021
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Rlss: A deep reinforcement learning algorithm for sequential scene generation
A. Ostonov, P. Wonka, and D. L. Michels · 2022
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