Fetching the paper…
Reading the bibliography…
Recent advances show that semi-supervised implicit representation learning can be achieved through physical constraints like Eikonal equations.
Joint 3d scene reconstruction and class segmentation
C. Hane, C. Zach, A. Cohen, R. Angst, and M. Pollefeys · 2013
Earlier work this paper cites.
Joint semantic segmentation and 3d reconstruction from monocular video
A. Kundu, Y. Li, F. Dellaert, F. Li, and J. M. Rehg · 2014
Earlier work this paper cites.
U-net: Convolutional networks for biomedical image segmentation
O. Ronneberger, P. Fischer, and T. Brox · 2015
Earlier work this paper cites.
Semantic scene completion from a single depth image
S. Song, F. Yu, A. Zeng, A. X. Chang, M. Savva, and T. Funkhouser · 2017
Earlier work this paper cites.
Physics inspired optimization on semantic transfer features: An alternative method for room layout estimation
H. Zhao, M. Lu, A. Yao, Y. Guo, Y. Chen, and L. Zhang · 2017
Earlier work this paper cites.
3d semantic segmentation with submanifold sparse convolutional networks
B. Graham, M. Engelcke, and L. Van Der Maaten · 2018
Earlier work this paper cites.
Efficient semantic scene completion network with spatial group convolution
J. Zhang, H. Zhao, A. Yao, Y. Chen, L. Zhang, and H. Liao · 2018
Earlier work this paper cites.
Semantickitti: A dataset for semantic scene understanding of lidar sequences
J. Behley, M. Garbade, A. Milioto, J. Quenzel, S. Behnke, C. Stachniss, and J. Gall · 2019
Earlier work this paper cites.
4d spatio-temporal convnets: Minkowski convolutional neural networks
C. Choy, J. Gwak, and S. Savarese · 2019
Earlier work this paper cites.
Rgbd based dimensional decomposition residual network for 3d semantic scene completion
J. Li, Y. Liu, D. Gong, Q. Shi, X. Yuan, C. Zhao, and I. Reid · 2019
Earlier work this paper cites.
Depth based semantic scene completion with position importance aware loss
J. Li, Y. Liu, X. Yuan, C. Zhao, R. Siegwart, I. Reid, and C. Cadena · 2019
Earlier work this paper cites.
Occupancy networks: Learning 3d reconstruction in function space
L. Mescheder, M. Oechsle, M. Niemeyer, S. Nowozin, and A. Geiger · 2019
Earlier work this paper cites.
Deepsdf: Learning continuous signed distance functions for shape representation
J. J. Park, P. Florence, J. Straub, R. Newcombe, and S. Lovegrove · 2019
Cited alongside, same era.
3d sketch-aware semantic scene completion via semi-supervised structure prior
X. Chen, K.-Y. Lin, C. Qian, G. Zeng, and H. Li · 2020
Cited alongside, same era.
Bsp-net: Generating compact meshes via binary space partitioning
Z. Chen, A. Tagliasacchi, and H. Zhang · 2020
Cited alongside, same era.
Local deep implicit functions for 3d shape
K. Genova, F. Cole, A. Sud, A. Sarna, and T. Funkhouser · 2020
Cited alongside, same era.
Nerf: Representing scenes as neural radiance fields for view synthesis
B. Mildenhall, P. P. Srinivasan, M. Tancik, J. T. Barron, R. Ramamoorthi, and R. Ng · 2020
Cited alongside, same era.
Convolutional occupancy networks
S. Peng, M. Niemeyer, L. Mescheder, M. Pollefeys, and A. Geiger · 2020
Learning continuous image representation with local implicit image function
Y. Chen, S. Liu, and X. Wang · 2021
Closest in time.
Mine: Towards continuous depth mpi with nerf for novel view synthesis
J. Li, Z. Feng, Q. She, H. Ding, C. Wang, and G. H. Lee · 2021
Closest in time.
Rfd-net: Point scene understanding by semantic instance reconstruction
Y. Nie, J. Hou, X. Han, and M. Nießner · 2021
Closest in time.
Giraffe: Representing scenes as compositional generative neural feature fields
M. Niemeyer and A. Geiger · 2021
Closest in time.
Giraffe: Representing scenes as compositional generative neural feature fields
M. Niemeyer and A. Geiger · 2021
Closest in time.
Nex: Real-time view synthesis with neural basis expansion
S. Wizadwongsa, P. Phongthawee, J. Yenphraphai, and S. Suwajanakorn · 2021
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
Spatial geometric reasoning for room layout estimation via deep reinforcement learning
L. Ren, Y. Song, J. Lu, and J. Zhou · 2020
Cited alongside, same era.
Lmscnet: Lightweight multiscale 3d semantic completion
L. Roldão, R. de Charette, and A. Verroust-Blondet · 2020
Cited alongside, same era.
Implicit neural representations with periodic activation functions
V. Sitzmann, J. Martel, A. Bergman, D. Lindell, and G. Wetzstein · 2020
Cited alongside, same era.
X. Yan, J. Gao, J. Li, R. Zhang, Z. Li, R. Huang, and S. Cui · 2020
Cited alongside, same era.
Pq-transformer: Jointly parsing 3d objects and layouts from point clouds
X. Chen, H. Zhao, G. Zhou, and Y.-Q. Zhang · 2021
Cited alongside, same era.
Closest in time.
Complete & label: A domain adaptation approach to semantic segmentation of lidar point clouds
L. Yi, B. Gong, and T. Funkhouser · 2021
Closest in time.
Plenoctrees for real-time rendering of neural radiance fields
A. Yu, R. Li, M. Tancik, H. Li, R. Ng, and A. Kanazawa · 2021
Closest in time.
Holistic 3d scene understanding from a single image with implicit representation
C. Zhang, Z. Cui, Y. Zhang, B. Zeng, M. Pollefeys, and S. Liu · 2021
Closest in time.
In-place scene labelling and understanding with implicit scene representation
S. Zhi, T. Laidlow, S. Leutenegger, and A. J. Davison · 2021
Closest in time.
Manhattan room layout reconstruction from a single 360 image: A comparative study of state-of-the-art methods
C. Zou, J.-W. Su, C.-H. Peng, A. Colburn, Q. Shan, P. Wonka, H.-K. Chu, and D. Hoiem · 2021
Closest in time.