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We propose InNeRF360, an automatic system that accurately removes text-specified objects from 360-degree Neural Radiance Fields (NeRF).
Shapenet: An information-rich 3d model repository
Angel X Chang, Thomas Funkhouser, Leonidas Guibas, Pat Hanrahan, Qixing Huang, Zimo Li, Silvio Savarese, Manolis Savva, Shuran Song, Hao Su, et al · 2015
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Context encoders: Feature learning by inpainting
Deepak Pathak, Philipp Krahenbuhl, Jeff Donahue, Trevor Darrell, and Alexei A Efros · 2016
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Mask r-cnn
Kaiming He, Georgia Gkioxari, Piotr Dollár, and Ross Girshick · 2017
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Gans trained by a two time-scale update rule converge to a local nash equilibrium
Martin Heusel, Hubert Ramsauer, Thomas Unterthiner, Bernhard Nessler, and Sepp Hochreiter · 2017
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Globally and locally consistent image completion
Satoshi Iizuka, Edgar Simo-Serra, and Hiroshi Ishikawa · 2017
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Local light field fusion: Practical view synthesis with prescriptive sampling guidelines
Ben Mildenhall, Pratul P Srinivasan, Rodrigo Ortiz-Cayon, Nima Khademi Kalantari, Ravi Ramamoorthi, Ren Ng, and Abhishek Kar · 2019
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Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
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Nerf: Representing scenes as neural radiance fields for view synthesis
Ben Mildenhall, Pratul P. Srinivasan, Matthew Tancik, Jonathan T. Barron, Ravi Ramamoorthi, and Ren Ng · 2020
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Mip-nerf: A multiscale representation for anti-aliasing neural radiance fields
Jonathan T Barron, Ben Mildenhall, Matthew Tancik, Peter Hedman, Ricardo Martin-Brualla, and Pratul P Srinivasan · 2021
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Rethinking space-time networks with improved memory coverage for efficient video object segmentation
Ho Kei Cheng, Yu-Wing Tai, and Chi-Keung Tang · 2021
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Nerf in the wild: Neural radiance fields for unconstrained photo collections
Ricardo Martin-Brualla, Noha Radwan, Mehdi SM Sajjadi, Jonathan T Barron, Alexey Dosovitskiy, and Daniel Duckworth · 2021
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Glide: Towards photorealistic image generation and editing with text-guided diffusion models
Alex Nichol, Prafulla Dhariwal, Aditya Ramesh, Pranav Shyam, Pamela Mishkin, Bob McGrew, Ilya Sutskever, and Mark Chen · 2021
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Learning transferable visual models from natural language supervision
Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, et al · 2021
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Ibrnet: Learning multi-view image-based rendering
Qianqian Wang, Zhicheng Wang, Kyle Genova, Pratul Srinivasan, Howard Zhou, Jonathan T. Barron, Ricardo Martin-Brualla, Noah Snavely, and Thomas Funkhouser · 2021
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Large scale image completion via co-modulated generative adversarial networks
Shengyu Zhao, Jonathan Cui, Yilun Sheng, Yue Dong, Xiao Liang, Eric I Chang, and Yan Xu · 2021
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Mip-nerf 360: Unbounded anti-aliased neural radiance fields
Jonathan T Barron, Ben Mildenhall, Dor Verbin, Pratul P Srinivasan, and Peter Hedman · 2022
Cited alongside, same era.
Diffedit: Diffusion-based semantic image editing with mask guidance
Guillaume Couairon, Jakob Verbeek, Holger Schwenk, and Matthieu Cord · 2022
Clip-mesh: Generating textured meshes from text using pretrained image-text models
Nasir Mohammad Khalid, Tianhao Xie, Eugene Belilovsky, and Tiberiu Popa · 2022
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Instant neural graphics primitives with a multiresolution hash encoding
Thomas Müller, Alex Evans, Christoph Schied, and Alexander Keller · 2022
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High-resolution image synthesis with latent diffusion models
Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer · 2022
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Palette: Image-to-image diffusion models
Chitwan Saharia, William Chan, Huiwen Chang, Chris Lee, Jonathan Ho, Tim Salimans, David Fleet, and Mohammad Norouzi · 2022
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Clip-nerf: Text-and-image driven manipulation of neural radiance fields
Can Wang, Menglei Chai, Mingming He, Dongdong Chen, and Jing Liao · 2022
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Instruct-nerf2nerf: Editing 3d scenes with instructions
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Cited alongside, same era.
Zero-shot text-guided object generation with dream fields
Ajay Jain, Ben Mildenhall, Jonathan T Barron, Pieter Abbeel, and Ben Poole · 2022
Cited alongside, same era.
Understanding pure clip guidance for voxel grid nerf models
Han-Hung Lee and Angel X Chang · 2022
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Grounded language-image pre-training
Liunian Harold Li, Pengchuan Zhang, Haotian Zhang, Jianwei Yang, Chunyuan Li, Yiwu Zhong, Lijuan Wang, Lu Yuan, Lei Zhang, Jenq-Neng Hwang, et al · 2022
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Nerf-in: Free-form nerf inpainting with rgb-d priors
Hao-Kang Liu, I Shen, Bing-Yu Chen, et al · 2022
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Latent-nerf for shape-guided generation of 3d shapes and textures
Gal Metzer, Elad Richardson, Or Patashnik, Raja Giryes, and Daniel Cohen-Or · 2022
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Text2mesh: Text-driven neural stylization for meshes
Oscar Michel, Roi Bar-On, Richard Liu, Sagie Benaim, and Rana Hanocka · 2022
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Laterf: Label and text driven object radiance fields
Ashkan Mirzaei, Yash Kant, Jonathan Kelly, and Igor Gilitschenski · 2022
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Ayaan Haque, Matthew Tancik, Alexei A. Efros, Aleksander Holynski, and Angjoo Kanazawa · 2023
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Segment anything
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Dinov2: Learning robust visual features without supervision, 2023
Maxime Oquab, Timothée Darcet, Theo Moutakanni, Huy V. Vo, Marc Szafraniec, Vasil Khalidov, Pierre Fernandez, Daniel Haziza, Francisco Massa, Alaaeldin El-Nouby, Russell Howes, Po-Yao Huang, Hu Xu, Vasu Sharma, Shang-Wen Li, Wojciech Galuba, Mike Rabbat, Mido Assran, Nicolas Ballas, Gabriel Synnaeve, Ishan Misra, Herve Jegou, Julien Mairal, Patrick Labatut, Armand Joulin, and Piotr Bojanowski · 2023
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Dreamfusion: Text-to-3d using 2d diffusion
Ben Poole, Ajay Jain, Jonathan T. Barron, and Ben Mildenhall · 2023
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Nerfstudio: A modular framework for neural radiance field development
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Nerfbusters: Removing ghostly artifacts from casually captured nerfs
Frederik Warburg*, Ethan Weber*, Matthew Tancik, Aleksander Hołyński, and Angjoo Kanazawa · 2023
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Removing objects from neural radiance fields
Silvan Weder, Guillermo Garcia-Hernando, Áron Monszpart, Marc Pollefeys, Gabriel J. Brostow, Michael Firman, and Sara Vicente · 2023
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