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We propose NeRF-VAE, a 3D scene generative model that incorporates geometric structure via NeRF and differentiable volume rendering.
Scene Representation Networks: Continuous 3D-Structure-Aware Neural Scene Representations
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Dream to Control: Learning Behaviors by Latent Imagination
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A volumetric method for building complex models from range images
Curless, B. and Levoy, M · 1996
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Light field rendering
Levoy, M. and Hanrahan, P · 1996
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BlockGAN: Learning 3D Object-aware Scene Representations from Unlabelled Images
Nguyen-Phuoc, T., Richardt, C., Mai, L., Yang, Y., and Mitra, N · 2002
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Multiple view geometry in computer vision (2. ed.)
Hartley, R. and Zisserman, A · 2003
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Distinctive Image Features from Scale-Invariant Keypoints
Lowe, D · 2004
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GRF: Learning a General Radiance Field for 3D Scene Representation and Rendering
Trevithick, A. and Yang, B · 2010
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Learning to Generate Chairs, Tables and Cars with Convolutional Networks
Dosovitskiy, A., Springenberg, J. T., Tatarchenko, M., and Brox, T · 2014
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LSD-SLAM: Large-Scale Direct Monocular SLAM
Engel, J., Schöps, T., and Cremers, D · 2014
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Adam: A method for stochastic optimization
Kingma, D. P. and Ba, J · 2014
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Auto-encoding variational bayes
Kingma, D. P. and Welling, M · 2014
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Stochastic Backpropagation and Approximate Inference in Deep Generative Models
Rezende, D. J., Mohamed, S., and Wierstra, D · 2014
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Single-view to Multi-view: Reconstructing Unseen Views with a Convolutional Network
Tatarchenko, M., Dosovitskiy, A., and Brox, T · 2015
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Identity Mappings in Deep Residual Networks
He, K., Zhang, X., Ren, S., and Sun, J · 2016
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Structure-from-Motion Revisited
Schönberger, J. L. and Frahm, J.-M · 2016
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Patches, Planes and Probabilities: A Non-Local Prior for Volumetric 3D Reconstruction
Ulusoy, A. O., Black, M. J., and Geiger, A · 2016
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BundleFusion: Real-time Globally Consistent 3D Reconstruction using On-the-fly Surface Re-integration
Dai, A., Nießner, M., Zollöfer, M., Izadi, S., and Theobalt, C · 2017
Cited alongside, same era.
A Learned Representation For Artistic Style
Dumoulin, V., Shlens, J., and Kudlur, M · 2017
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CLEVR: A Diagnostic Dataset for Compositional Language and Elementary Visual Reasoning
Johnson, J., Hariharan, B., van der Maaten, L., Fei-Fei, L., Lawrence Zitnick, C., and Girshick, R · 2017
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Learning to Synthesize a 4D RGBD Light Field from a Single Image
Srinivasan, P. P., Wang, T., Sreelal, A., Ramamoorthi, R., and Ng, R · 2017
Cited alongside, same era.
Attention is all you need
HoloGAN: Unsupervised Learning of 3D Representations From Natural Images
Nguyen-Phuoc, T., Li, C., Theis, L., Richardt, C., and Yang, Y · 2019
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Neural Radiance Flow for 4D View Synthesis and Video Processing
Du, Y., Zhang, Y., Yu, H.-X., Tenenbaum, J., and Wu, J · 2020
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Squeeze-and-Excitation Networks
Hu, J., Shen, L., Albanie, S., Sun, G., and Wu, E · 2020
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Neural Scene Flow Fields for Space-Time View Synthesis of Dynamic Scenes
Li, Z., Niklaus, S., Snavely, N., and Wang, O · 2020
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NeRF in the Wild: Neural radiance fields for unconstrained photo collections
Martin-Brualla, R., Radwan, N., Sajjadi, M. S., Barron, J. T., Dosovitskiy, A., and Duckworth, D · 2020
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NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis
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Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A. N., Kaiser, Ł., and Polosukhin, I · 2017
Cited alongside, same era.
Inference Suboptimality in Variational Autoencoders
Cremer, C., Li, X., and Duvenaud, D · 2018
Cited alongside, same era.
Neural scene representation and rendering
Eslami, S. A., Rezende, D. J., Besse, F., Viola, F., Morcos, A. S., Garnelo, M., Ruderman, A., Rusu, A. A., Danihelka, I., Gregor, K., et al · 2018
Cited alongside, same era.
Semi-Amortized Variational Autoencoders
Kim, Y., Wiseman, S., Miller, A., Sontag, D., and Rush, A. M · 2018
Cited alongside, same era.
Iterative Amortized Inference
Marino, J., Yue, Y., and Mandt, S · 2018
Cited alongside, same era.
Generalized ELBO with Constrained Optimization, GECO
Rezende, D. J. and Viola, F · 2018
Cited alongside, same era.
Stereo magnification: learning view synthesis using multiplane images
Zhou, T., Tucker, R., Flynn, J., Fyffe, G., and Snavely, N · 2018
Cited alongside, same era.
Mildenhall, B., Srinivasan, P. P., Tancik, M., Barron, J. T., Ramamoorthi, R., and Ng, R · 2020
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GIRAFFE: Representing Scenes as Compositional Generative Neural Feature Fields
Niemeyer, M. and Geiger, A · 2020
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Deformable Neural Radiance Fields
Park, K., Sinha, U., Barron, J., Bouaziz, S., Goldman, D., Seitz, S., and Brualla, R.-M · 2020
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D-NeRF: Neural Radiance Fields for Dynamic Scenes
Pumarola, A., Corona, E., Pons-Moll, G., and Moreno-Noguer, F · 2020
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GRAF: Generative Radiance Fields for 3D-Aware Image Synthesis
Schwarz, K., Liao, Y., Niemeyer, M., and Geiger, A · 2020
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Learned Initializations for Optimizing Coordinate-Based Neural Representations
Tancik, M., Mildenhall, B., Wang, T., Schmidt, D., Srinivasan, P. P., Barron, J., and Ng, R · 2020
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NVAE: A Deep Hierarchical Variational Autoencoder
Vahdat, A. and Kautz, J · 2020
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Space-time Neural Irradiance Fields for Free-Viewpoint Video
Xian, W., Huang, J., Kopf, J., and Kim, C · 2020
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pixelNeRF: Neural Radiance Fields from One or Few Images
Yu, A., Ye, V., Tancik, M., and Kanazawa, A · 2020
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Bottleneck Transformers for Visual Recognition
Srinivas, A., Lin, T.-Y., Parmar, N., Shlens, J., Abbeel, P., and Vaswani, A · 2021
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