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Large language and vision models have been leading a revolution in visual computing.
A probabilistic framework for surface reconstruction from multiple images
Motilal Agrawal and Larry S Davis · 2001
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A probabilistic framework for space carving
Adrian Broadhurst, Tom W Drummond, and Roberto Cipolla · 2001
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Efficient variants of the icp algorithm
Szymon Rusinkiewicz and Marc Levoy · 2001
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Fast point feature histograms (FPFH) for 3D registration
Radu Bogdan Rusu, Nico Blodow, and Michael Beetz · 2009
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Patchmatch stereo-stereo matching with slanted support windows
Michael Bleyer, Christoph Rhemann, and Carsten Rother · 2011
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Depth map prediction from a single image using a multi-scale deep network
David Eigen, Christian Puhrsch, and Rob Fergus · 2014
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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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Sun rgb-d: A rgb-d scene understanding benchmark suite
Shuran Song, Samuel P Lichtenberg, and Jianxiong Xiao · 2015
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Scannet: Richly-annotated 3d reconstructions of indoor scenes
Angela Dai, Angel X Chang, Manolis Savva, Maciej Halber, Thomas Funkhouser, and Matthias Nießner · 2017
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Mask r-cnn
Kaiming He, Georgia Gkioxari, Piotr Dollár, and Ross Girshick · 2017
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Pix3D: Dataset and methods for single-image 3d shape modeling
Xingyuan Sun, Jiajun Wu, Xiuming Zhang, Zhoutong Zhang, Chengkai Zhang, Tianfan Xue, Joshua B Tenenbaum, and William T Freeman · 2018
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Mesh r-cnn
Georgia Gkioxari, Jitendra Malik, and Justin Johnson · 2019
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Roberta: A robustly optimized bert pretraining approach
Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, and Veselin Stoyanov · 2019
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Occupancy networks: Learning 3D reconstruction in function space
Lars Mescheder, Michael Oechsle, Michael Niemeyer, Sebastian Nowozin, and Andreas Geiger · 2019
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DeepSDF: Learning continuous signed distance functions for shape representation
Jeong Joon Park, Peter Florence, Julian Straub, Richard Newcombe, and Steven Lovegrove · 2019
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The replica dataset: A digital replica of indoor spaces
Julian Straub, Thomas Whelan, Lingni Ma, Yufan Chen, Erik Wijmans, Simon Green, Jakob J Engel, Raul Mur-Artal, Carl Ren, Shobhit Verma, et al · 2019
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Language models are few-shot learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al · 2020
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An image is worth 16x16 words: Transformers for image recognition at scale
Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn, Xiaohua Zhai, Thomas Unterthiner, Mostafa Dehghani, Matthias Minderer, Georg Heigold, Sylvain Gelly, et al · 2020
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NeRF: Representing scenes as neural radiance fields for view synthesis
B Mildenhall, PP Srinivasan, M Tancik, JT Barron, R Ramamoorthi, and R Ng · 2020
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Total3dunderstanding: Joint layout, object pose and mesh reconstruction for indoor scenes from a single image
Yinyu Nie, Xiaoguang Han, Shihui Guo, Yujian Zheng, Jian Chang, and Jian Jun Zhang · 2020
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Exploring the limits of transfer learning with a unified text-to-text transformer
Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J Liu · 2020
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Towards robust monocular depth estimation: Mixing datasets for zero-shot cross-dataset transfer
René Ranftl, Katrin Lasinger, David Hafner, Konrad Schindler, and Vladlen Koltun · 2020
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Beit: Bert pre-training of image transformers
Hangbo Bao, Li Dong, Songhao Piao, and Furu Wei · 2021
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Unsupervised learning of fine structure generation for 3D point clouds by 2D projections matching
Chao Chen, Zhizhong Han, Yu-Shen Liu, and Matthias Zwicker · 2021
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Panoptic 3d scene reconstruction from a single rgb image
Manuel Dahnert, Ji Hou, Matthias Nießner, and Angela Dai · 2021
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Omnidata: A scalable pipeline for making multi-task mid-level vision datasets from 3d scans
Ainaz Eftekhar, Alexander Sax, Jitendra Malik, and Amir Zamir · 2021
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3d-front: 3d furnished rooms with layouts and semantics
Huan Fu, Bowen Cai, Lin Gao, Ling-Xiao Zhang, Jiaming Wang, Cao Li, Qixun Zeng, Chengyue Sun, Rongfei Jia, Binqiang Zhao, et al · 2021
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3d-future: 3d furniture shape with texture
Huan Fu, Rongfei Jia, Lin Gao, Mingming Gong, Binqiang Zhao, Steve Maybank, and Dacheng Tao · 2021
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Openclip, July 2021
Gabriel Ilharco, Mitchell Wortsman, Ross Wightman, Cade Gordon, Nicholas Carlini, Rohan Taori, Achal Dave, Vaishaal Shankar, Hongseok Namkoong, John Miller, Hannaneh Hajishirzi, Ali Farhadi, and Ludwig Schmidt · 2021
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Sdedit: Guided image synthesis and editing with stochastic differential equations
Chenlin Meng, Yutong He, Yang Song, Jiaming Song, Jiajun Wu, Jun-Yan Zhu, and Stefano Ermon · 2021
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Unisurf: Unifying neural implicit surfaces and radiance fields for multi-view reconstruction
Michael Oechsle, Songyou Peng, and Andreas Geiger · 2021
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Shape as points: A differentiable poisson solver
Songyou Peng, Chiyu Jiang, Yiyi Liao, Michael Niemeyer, Marc Pollefeys, and Andreas Geiger · 2021
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Learning 3d scene priors with 2d supervision
Yinyu Nie, Angela Dai, Xiaoguang Han, and Matthias Nießner · 2023
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EVA-CLIP: Improved training techniques for clip at scale
Quan Sun, Yuxin Fang, Ledell Wu, Xinlong Wang, and Yue Cao · 2023
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Llama: Open and efficient foundation language models
Hugo Touvron, Thibaut Lavril, Gautier Izacard, Xavier Martinet, Marie-Anne Lachaux, Timothée Lacroix, Baptiste Rozière, Naman Goyal, Eric Hambro, Faisal Azhar, et al · 2023
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Pointllm: Empowering large language models to understand point clouds
Runsen Xu, Xiaolong Wang, Tai Wang, Yilun Chen, Jiangmiao Pang, and Dahua Lin · 2023
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Metric3D: Towards zero-shot metric 3d prediction from a single image
Wei Yin, Chi Zhang, Hao Chen, Zhipeng Cai, Gang Yu, Kaixuan Wang, Xiaozhi Chen, and Chunhua Shen · 2023
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Learning transferable visual models from natural language supervision
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NeuS: Learning neural implicit surfaces by volume rendering for multi-view reconstruction
Peng Wang, Lingjie Liu, Yuan Liu, Christian Theobalt, Taku Komura, and Wenping Wang · 2021
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Volume rendering of neural implicit surfaces
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Neural rgb-d surface reconstruction
Dejan Azinović, Ricardo Martin-Brualla, Dan B Goldman, Matthias Nießner, and Justus Thies · 2022
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EVA: Exploring the limits of masked visual representation learning at scale
Yuxin Fang, Wen Wang, Binhui Xie, Quan Sun, Ledell Wu, Xinggang Wang, Tiejun Huang, Xinlong Wang, and Yue Cao · 2022
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Masked autoencoders are scalable vision learners
Kaiming He, Xinlei Chen, Saining Xie, Yanghao Li, Piotr Dollár, and Ross Girshick · 2022
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3d common corruptions and data augmentation
Oğuzhan Fatih Kar, Teresa Yeo, Andrei Atanov, and Amir Zamir · 2022
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Fast learning radiance fields by shooting much fewer rays
Wenyuan Zhang, Ruofan Xing, Yunfan Zeng, Yu-Shen Liu, Kanle Shi, and Zhizhong Han · 2023
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Uni-3D: A universal model for panoptic 3D scene reconstruction
Xiang Zhang, Zeyuan Chen, Fangyin Wei, and Zhuowen Tu · 2023
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Learning a more continuous zero level set in unsigned distance fields through level set projection
Junsheng Zhou, Baorui Ma, Shujuan Li, Yu-Shen Liu, and Zhizhong Han · 2023
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Differentiable registration of images and lidar point clouds with voxelpoint-to-pixel matching
Junsheng Zhou, Baorui Ma, Wenyuan Zhang, Yi Fang, Yu-Shen Liu, and Zhizhong Han · 2023
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Binocular-guided 3d gaussian splatting with view consistency for sparse view synthesis
Liang Han, Junsheng Zhou, Yu-Shen Liu, and Zhizhong Han · 2024
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NeuSurf: On-surface priors for neural surface reconstruction from sparse input views
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Music-udf: Learning multi-scale dynamic grid representation for high-fidelity surface reconstruction from point clouds
Chuan Jin, Tieru Wu, Yu-Shen Liu, and Junsheng Zhou · 2024
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Repurposing diffusion-based image generators for monocular depth estimation
Bingxin Ke, Anton Obukhov, Shengyu Huang, Nando Metzger, Rodrigo Caye Daudt, and Konrad Schindler · 2024
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Learning continuous implicit field with local distance indicator for arbitrary-scale point cloud upsampling
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One-2-3-45: Any single image to 3d mesh in 45 seconds without per-shape optimization
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MultiPull: Detailing signed distance functions by pulling multi-level queries at multi-step
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Depth anything: Unleashing the power of large-scale unlabeled data
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Lihe Yang, Bingyi Kang, Zilong Huang, Zhen Zhao, Xiaogang Xu, Jiashi Feng, and Hengshuang Zhao · 2024
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Neural signed distance function inference through splatting 3d gaussians pulled on zero-level set
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Learning unsigned distance functions from multi-view images with volume rendering priors
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Cap-udf: Learning unsigned distance functions progressively from raw point clouds with consistency-aware field optimization
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Fast learning of signed distance functions from noisy point clouds via noise to noise mapping
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Uni3D: Exploring Unified 3D Representation at Scale
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3d-oae: Occlusion auto-encoders for self-supervised learning on point clouds
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Diffgs: Functional gaussian splatting diffusion
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Udiff: Generating conditional unsigned distance fields with optimal wavelet diffusion
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