Recent Papers in 3D Computer Vision
Some research works related to 3D computer vision, published in the recent top venues. Lists and details to be extended…
ECCV 2016
Structure-from-Motion and Pose Estimation:
- Tianwei Shen, Siyu Zhu, Tian Fang, Runze Zhang, Long Quan, Graph-Based Consistent Matching for Structure-from-Motion.
As you have noticed, this is my paper :). We propose a new method of matching image collections for SfM, which improves the matching efficiency as well as coping with ambiguous scenes. Leave a comment (at the bottom of this page) if you are interested.
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Je Hyeong Hong, Christopher Zach, Andrew Fitzgibbon, Roberto Cipolla. Projective Bundle Adjustment from Arbitrary Initialization using the Variable Projection Method.
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Jonathan Ventura. Structure from Motion on a Sphere.
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Gaku Nakano. A Versatile Approach for Solving PnP, PnPf, and PnPfr Problems.
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Cenek Albl, Akihiro Sugimoto, Tomas Pajdla, Degeneracies in Rolling Shutter SfM.
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Gim Hee Lee. A Minimal Solution for Non-Perspective Pose Estimation from Line Correspondences.
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Federico Camposeco, Torsten Sattler, Marc Pollefeys, Minimal Solvers for Generalized Pose and Scale Estimation from Two Rays and One Point.
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Pose Estimation Errors, the Ultimate Diagnosis.
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Kyle Wilson, David Bindel, Noah Snavely. When is Rotations Averaging Hard?
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ShapeFit and ShapeKick for Robust, Scalable Structure from Motion.
Another translation averaging method based on ADMM.
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Branching Gaussian Processes with Applications to Spatiotemporal Reconstruction of 3D Trees
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Accurate and Linear Time Pose Estimation from Points and Lines.
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Robust and Accurate Line- and/or Point-Based Pose Estimation without Manhattan Assumptions.
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\piMatch: Monocular vSLAM and Piecewise Planar Reconstruction using Fast Plane Correspondences
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Bayesian Image based 3D Pose Estimation
Stereo:
This is kind of a promotion for my friend and labmate Shiwei’s work. They have done excellent work on multi-view stereo which powers the 3D reconstruction engine of Altizure, take a look the paper if you are interested:).
The results are quite impressive, including a video for demonstration.
- Fabian Langguth, Kalyan Sunkavalli, Sunil Hadap, Michael Goesele. Shading-aware Multi-view Stereo.
Reconstruction:
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Indoor-Outdoor 3D Reconstruction Alignment
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Minglei Li, Peter Wonka, Liangliang Nan. Manhattan-world Urban Reconstruction from Point Clouds.
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Lama Affara, Liangliang Nan, Bernard Ghanem, Peter Wonka. Large Scale Asset Extraction for Urban Images.
The information for the above two papers can be accessed here.
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Federica Arrigoni, Beatrice Rossi, Andrea Fusiello. Global Registration of 3D Point Sets via LRS decomposition.
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Liuyun Duan, Florent Lafarge. Towards large-scale city reconstruction from satellites.
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Hanme Kim, Stefan Leutenegger, Andrew Davison. Real-Time 3D Reconstruction and 6-DoF Tracking with an Event Camera.
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Template-free 3D Reconstruction of Poorly-textured Nonrigid Surfaces
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Real-time Large-Scale Dense 3D Reconstruction with Loop Closure.
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3D-R2N2: A unified approach for single and multi-view 3D object reconstruction.
Feature and Matching:
This is a very interesting work that obtains local feature with deep neural nets. I am looking forward to the code.
- Nam Vo, James Hays. Localizing and Orienting Street Views Using Overhead Imagery.
Matching ground-level image with overhead imagery using CNN
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Yoni Kasten, Gil Ben-Artzi, Shmuel Peleg, Michael Werman. Fundamental Matrices from Moving Objects Using Line Motion Barcodes.
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Wen-Yan Lin, Siying Liu, Nianjuan Jiang, Minh Do, Ping Tan, Jiangbo Lu. RepMatch: Robust Feature Matching and Pose for Reconstructing Modern Cities.
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Amir R. Zamir, Pulkit Agrawal, Tilman Wekel, Jitendra Malik, Silvio Savarese. Generic 3D Representations via Pose Estimation and Matching. (DL)
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Avi Kaplan, Tamar Avraham, Michael Lindenbaum. Interpreting the Ratio Criterion for Matching SIFT Descriptors,
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Guacn Long, Laurent Kneip, Jose M. Alvarez, Hongdong Li, Xiaohu Zhang, Qifeng Yu. Learning Image Matching by Simply Watching Video.
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Guided Matching based on Statistical Optical Flow for Fast and Robust Correspondence Analysis.
Image Retrieval:
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Filip Radenovic, Giorgos Tolias, Ondra Chum. CNN Image Retrieval Learns from BoW: Unsupervised Fine-Tuning with Hard Examples (oral)
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Xiaohan Fei, Konstantine Tsotsos, Stefano Soatto. A Simple Hierarchical Pooling Data Structure for Loop Closure.
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Albert Gordo, Jon Almazan, Jerome Revaud, Diane Larlus. Deep Image Retrieval: Learning Global Representations for Image Search.
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Kernel-Based Supervised Discrete Hashing for Image Retrieval
CVPR 2016
Reconstruction:
- ***Vo, M., Narasimhan, S. G., & Sheikh, Y. Spatiotemporal Bundle Adjustment for Dynamic 3D Reconstruction.
Project website, 强烈推荐video,演员十分癫狂…
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Hao Wang, Jun Wang, Wang Liang. Online Reconstruction of Indoor Scenes From RGB-D Streams.
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Ali Osman Ulusoy, Michael J. Black, Andreas Geiger. Patches, Planes and Probabilities: A Non-Local Prior for Volumetric 3D Reconstruction.
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Olivier Saurer, Marc Pollefeys, Gim Hee Lee. Sparse to Dense 3D Reconstruction From Rolling Shutter Images.
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**Filip Radenovic, Johannes L. Schönberger, Dinhuang Ji, Jan-Michael Frahm, Ondrej Chum, Jiri Matas. From Dusk till Dawn: Modeling in the Dark
A method to cope with illumination changes in Internet dataset. After camera registration, a clustering method is applied and seperate the scene graph into the Day cluster and the Night cluster. Dense models are reconstruction seperately, following a fusion process. (sparse -> dense)
- Fan, Bin, et al. “Do We Need Binary Features for 3D Reconstruction?.”
This paper discusses whether it is necessary to use binary features in 3D reconstruction.
Structure-from-Motion:
- ***Johannes L. Schönberger, Jan-Michael Frahm. Structure-From-Motion Revisited.
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A Consensus-Based Framework for Distributed Bundle Adjustment
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A Direct Least-Squares Solution to the PnP Problem With Unknown Focal Length.
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Marco Crocco, Cosimo Rubino, Alessio Del Bue. Structure From Motion With Objects.
Feature and Matching:
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Using Spatial Order to Boost the Elimination of Incorrect Feature Matches
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***Tsun-Yi Yang, Yen-Yu Lin, Yung-Yu Chuang. Accumulated Stability Voting - A Robust Descriptor From Descriptors of Multiple Scales.
Project website: worth trying since there is code available.
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Swarna K. Ravindran, Anurag Mittal. CoMaL - Good Features to Match on Object Boundaries.
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Yuan-Ting Hu, Yen-Yu Lin. Progressive Feature Matching With Alternate Descriptor Selection and Correspondence Enrichment.
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Angjoo Kanazawa, David W. Jacobs, Manmohan Chandraker. WarpNet: Weakly Supervised Matching for Single-View Reconstruction. (DL)
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Jin Xie, Meng Wang, Yi Fang. Learned Binary Spectral Shape Descriptor for 3D Shape Correspondence.
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Zhou, Tinghui, et al. “Learning Dense Correspondence via 3D-guided Cycle Consistency.” (DL)
Retrieval:
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Haomiao Liu, Ruiping Wang, Shiguang Shan, Xilin Chen. Deep Supervised Hashing for Fast Image Retrieval. (DL)
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Eng-Jon Ong, Miroslaw Bober. Improved Hamming Distance Search Using Variable Length Substrings.
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Jae-Pil Heo, Zhe Lin, Xiaohui Shen, Jonathan Brandt, Sung-eui Yoon. Shortlist Selection With Residual-Aware Distance Estimator for K-Nearest Neighbor Search.
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Xiaojuan Wang, Ting Zhang, Guo-Jun Qi, Jinhui Tang, Jingdong Wang. Supervised Quantization for Similarity Search .
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Patrick Wieschollek, Oliver Wang, Alexander Sorkine-Hornung, Hendrik P. A. Lensch. Efficient Large-Scale Approximate Nearest Neighbor Search on the GPU.
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Ting Zhang, Jingdong Wang. Collaborative Quantization for Cross-Modal Similarity Search.
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Thi Quynh Nhi Tran, Hervé Le Borgne, Michel Crucianu. Aggregating Image and Text Quantized Correlated Components.
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Artem Babenko, Victor Lempitsky. Efficient Indexing of Billion-Scale Datasets of Deep Descriptors.
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***Ahmet Iscen, Michael Rabbat, Teddy Furon. Efficient Large-Scale Similarity Search Using Matrix Factorization.
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Theodora Kontogianni, Markus Mathias, Bastian Leibe. Incremental Object Discovery in Time-Varying Image Collections.
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Torsten Sattler, Michal Havlena, Konrad Schindler, Marc Pollefeys. Large-Scale Location Recognition and the Geometric Burstiness Problem.
Stereo:
- Alex Locher, Michal Perdoch, Luc Van Gool. Progressive Prioritized Multi-View Stereo.
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Cédric Verleysen, Christophe De Vleeschouwer. Piecewise-Planar 3D Approximation From Wide-Baseline Stereo.
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John Flynn, Ivan Neulander, James Philbin, Noah Snavely. DeepStereo: Learning to Predict New Views From the World’s Imagery.
Accepted in CVPR 2016 but released a year ago (2015), see the video
Segmentation and Scene Understanding:
- Ole Johannsen, Antonin Sulc, Bastian Goldluecke. What Sparse Light Field Coding Reveals About Scene Structure.
Calibration
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Ian Schillebeeckx, Robert Pless. Single Image Camera Calibration With Lenticular Arrays for Augmented Reality.
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Andrey Bushnevskiy, Lorenzo Sorgi, Bodo Rosenhahn. Multicamera Calibration From Visible and Mirrored Epipoles.
Pose, Rolling Shutter & Other:
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Eric Brachmann, Frank Michel, Alexander Krull, Michael Ying Yang, Stefan Gumhold, Carsten Rother. Uncertainty-Driven 6D Pose Estimation of Objects and Scenes From a Single RGB Image.
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Cenek Albl, Zuzana Kukelova, Tomas Pajdla. Rolling Shutter Absolute Pose Problem With Known Vertical Direction.
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Compute epipolar geometry and correspondences at the same time, theoretically interesting.
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Luca Magri, Andrea Fusiello. Multiple Model Fitting as a Set Coverage Problem.
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Matthew Trager, Martial Hebert, Jean Ponce. Consistency of Silhouettes and Their Duals.
ICCV 2015
Tracking and Localization:
- Joseph Tan, D., Tombari, F., Ilic, S., & Navab, N. (2015). A Versatile Learning-Based 3D Temporal Tracker: Scalable, Robust, Online.
A tracking algorithm using depth images
Optimization
- Diamond, S., & Boyd, S. (2015). Convex Optimization With Abstract Linear Operators.
CVX, Cone programming, linear transform
SfM and Visual SLAM
- Jose Tarrio, J., & Pedre, S. (2015). Realtime Edge-Based Visual Odometry for a Monocular Camera.
Edge feature based visual odometry with code
- Johannsen, O., Sulc, A., & Goldluecke, B. (2015). On Linear Structure from Motion for Light Field Cameras.
An application of Lytro cinema.
- Cui, Zhaopeng, and Ping Tan. “Global Structure-from-Motion by Similarity Averaging.”
Yet another global method for SfM
Stereo
- Benjamin Ummenhofer and Thomas Brox. Global, Dense Multiscale Reconstruction for a Billion Points.
Multi-scale surface reconstruction. Video
Reconstruction
- Martin-Brualla, R., Gallup, D., & Seitz, S. M. (2015). 3D Time-Lapse Reconstruction from Internet Photos.
Given an Internet photo collection of a landmark, we compute a 3D time-lapse video sequence where a virtual camera moves continuously in time and space. Project website
- Ikehata, S., Yang, H., & Furukawa, Y. (2015). Structured Indoor Modeling.
Project website, with matlab code and datasets.
- Zheng, Enliang, et al. Minimal Solvers for 3D Geometry from Satellite Imagery.
Pose, Point Cloud & Others
- Katz, S., & Tal, A. (2015). On the Visibility of Point Clouds.
determine the visible subset of points directly from a given point cloud
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Rhodin, H., Robertini, N., Richardt, C., Seidel, H. P., & Theobalt, C. (2015). A Versatile Scene Model with Differentiable Visibility Applied to Generative Pose Estimation.
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Ventura, Jonathan, Clemens Arth, and Vincent Lepetit. “An Efficient Minimal Solution for Multi-Camera Motion.”
*Code
CVPR 2015
SfM and Localization:
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Lin, Tsung-Yi, et al. “Learning deep representations for ground-to-aerial geolocalization.”
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Song, S., & Chandraker, M. (2015). Joint SFM and detection cues for monocular 3D localization in road scenes.
Reconstruction:
- **Choi, Sungjoon, Qian-Yi Zhou, and Vladlen Koltun. “Robust reconstruction of indoor scenes.”
Indoor scene reconstruction from RGB-D video, with code and dataset available.
Stereo:
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Savinov, Nikolay, Christian Hane, and Marc Pollefeys. “Discrete optimization of ray potentials for semantic 3D reconstruction.”
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Jung, J., Lee, J. Y., & Kweon, I. S. (2015, June). One-day outdoor photometric stereo via skylight estimation.
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Xie, W., Dai, C., & Wang, C. C. (2015, June). Photometric stereo with near point lighting: A solution by mesh deformation.
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Li, Zhuwen, et al. “Simultaneous video defogging and stereo reconstruction.”
Feature and Matching:
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*Litman, Roee, et al. “Inverting RANSAC: Global Model Detection via Inlier Rate Estimation.”
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Dong, Jingming, and Stefano Soatto. “Domain-size pooling in local descriptors: DSP-SIFT.”
http://vision.ucla.edu/~jingming/proj/dsp/
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**Yumin Suh, Kamil Adamczewski, Kyoung Mu Lee. “Subgraph Matching Using Compactness Prior for Robust Feature Correspondence”
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Yanchao Yang, Zhaojin Lu, Ganesh Sundaramoorthi. “Coarse-To-Fine Region Selection and Matching”
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Faraki, Masoud, Mehrtash T. Harandi, and Fatih Porikli. “More About VLAD: A Leap from Euclidean to Riemannian Manifolds.”
Retrieval:
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***Li, Xinchao, Martha Larson, and Alan Hanjalic. “Pairwise geometric matching for large-scale object retrieval.”
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Jiang, Ke, Qichao Que, and Brian Kulis. “Revisiting kernelized locality-sensitive hashing for improved large-scale image retrieval.”
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**Johnson, Justin, et al. “Image retrieval using scene graphs.” Computer Vision and Pattern Recognition (CVPR), 2015.
sementic image retrieval
3D with Sensors:
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Ye, M., Zhang, Y., Yang, R., & Manocha, D. “3d reconstruction in the presence of glasses by acoustic and stereo fusion.”
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Gupta, S., Arbeláez, P., Girshick, R., & Malik, J. “Aligning 3D models to RGB-D images of cluttered scenes.”
Segmentation and Scene Understanding:
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Wang, S., Fidler, S., & Urtasun, R. (2015, June). Holistic 3d scene understanding from a single geo-tagged image.
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Martinovic, Andelo, et al. “3d all the way: Semantic segmentation of urban scenes from start to end in 3d.”