Automatic photo pop-up

Untitled work

(1992) · Cited by 23,431

Multiple View Geometry in Computer Vision

Hartley, R., & Zisserman, A. (2004) · doi:10.1017/cbo9780511811685 · Cited by 21,070

Pattern Classification

Seel, N. M. (2012) · Springer eBooks · doi:10.1007/978-1-4419-1428-6_5195 · Cited by 19,482

A database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics

Martin, D., Fowlkes, C., Tal, D., & Malik, J. (2002) · Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001 · doi:10.1109/iccv.2001.937655 · Cited by 8,216

Additive logistic regression: a statistical view of boosting (with discussion and a rejoinder by the authors)

Friedman, J., Hastie, T., & Tibshirani, R. (2000) · The Annals of Statistics · doi:10.1214/aos/1016218223 · Cited by 6,884

Use of the hough transformation to detect lines and curves in pictures

Duda, R. O., & Hart, P. E. (1972) · Communications of the ACM · doi:10.1145/361237.361242 · Cited by 6,633

Efficient Graph-Based Image Segmentation

Felzenszwalb, P. F., & Huttenlocher, D. P. (2004) · International Journal of Computer Vision · doi:10.1023/b:visi.0000022288.19776.77 · Cited by 6,205

Light field rendering

Levoy, M., & Hanrahan, P. (1996) · ACM SIGGRAPH Annual Conference on Computer Graphics and Interactive Techniques (SIGGRAPH) · doi:10.1145/237170.237199 · Cited by 3,789

Multiple View Geometry in Computer Vision (2nd ed)

Hartley, R. I., & Zisserman, A. (2003) · Cambridge University Press eBooks · Cited by 2,747

The lumigraph

Gortler, S. J., Grzeszczuk, R., Szeliski, R., & Cohen, M. F. (1996) · ACM SIGGRAPH Conference (SIGGRAPH) · doi:10.1145/237170.237200 · Cited by 2,459

Insitu

Paczkowski, P., Kim, M. H., Morvan, Y., Dorsey, J. O., Rushmeier, H., & O’Sullivan, C. (2011) · ACM SIGGRAPH Conference and Exhibition on Computer Graphics and Interactive Techniques in Asia (SIGGRAPH Asia) · doi:10.1145/2024156.2024216 · Cited by 26

Diffusion Handles Enabling 3D Edits for Diffusion Models by Lifting Activations to 3D

Pandey, K., Guerrero, P., Gadelha, M., Hold-Geoffroy, Y., Singh, K., & Mitra, N. J. (2024) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr52733.2024.00735 · Cited by 35

Single Image Depth Estimation Using Deep Adversarial Training

Hambarde, P., Dudhane, A. A., & Murala, S. (2019) · Proceedings - International Conference on Image Processing · doi:10.1109/icip.2019.8803027 · Cited by 25

Few-Shot Single-View 3-D Object Reconstruction with Compositional Priors

Michalkiewicz, M., Parisot, S., Tsogkas, S., Baktashmotlagh, M., Eriksson, A. P., & Belilovsky, E. (2020) · Lecture notes in computer science · doi:10.1007/978-3-030-58595-2_37 · Cited by 26

Interactive 3D building modeling method using panoramic image sequences and digital map

Kim, H., & Han, S. (2018) · Multimedia Tools and Applications · doi:10.1007/s11042-018-5926-4 · Cited by 25

An image segmentation method using logarithmic kbest gravitational search algorithm based superpixel clustering

Mittal, H., & Saraswat, M. (2018) · Evolutionary Intelligence · doi:10.1007/s12065-018-0192-y · Cited by 25

What, Where and Who? Telling the Story of an Image by Activity Classification, Scene Recognition and Object Categorization

Fei-Fei, L., & Li, L.-J. (2010) · Studies in computational intelligence · doi:10.1007/978-3-642-12848-6_6 · Cited by 24

Flower reconstruction from a single photo

Yan, F., Gong, M., Cohen‐Or, D., Deußen, O., & Chen, B. (2014) · Computer Graphics Forum · doi:10.1111/cgf.12332 · Cited by 24

Single-Image 3-D Reconstruction: Rethinking Point Cloud Deformation

Nguyen, D. C., Choi, S., Kim, W., Kim, J., Oh, H., Kang, J., & Lee, S. (2022) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2022.3211929 · Cited by 25

Learning shape priors for single view reconstruction

Chen, Y., & Cipolla, R. (2009) · IEEE International Conference on Computer Vision Workshops · doi:10.1109/iccvw.2009.5457443 · Cited by 24

Monocular Extraction of 2.1D Sketch Using Constrained Convex Optimization

Amer, M. R., Yousefi, S., Raich, R., & Todorović, S. (2014) · International Journal of Computer Vision · doi:10.1007/s11263-014-0752-2 · Cited by 24

Monocular depth estimation with guidance of surface normal map

Han, Y., Zhang, S., Zhang, Y., & Zhang, L. (2017) · Neurocomputing · doi:10.1016/j.neucom.2017.08.074 · Cited by 24

3-D Reconstruction from Sparse Views using Monocular Vision

Saxena, A., Sun, M., & Ng, A. Y. (2007) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2007.4409219 · Cited by 24

Predicting Eye Fixations With Higher-Level Visual Features

Liang, M., & Hu, X. (2015) · IEEE Transactions on Image Processing · doi:10.1109/tip.2015.2395713 · Cited by 23

Simultaneous Segmentation and Figure/Ground Organization Using Angular Embedding

Maire, M. (2010) · Lecture notes in computer science · doi:10.1007/978-3-642-15552-9_33 · Cited by 22

A Survey on Video-based Graphics and Video Visualization

Borgo, R., Chen, M., Daubney, B., Grundy, E., Heidemann, G., Höferlin, B., Höferlin, M., Jänicke, H., Weiskopf, D., & Xie, X. (2011) · doi:10.2312/eg2011/stars/001-023 · Cited by 23

Static Scene Illumination Estimation from Videos with Applications

Liu, B., Xu, K., & Martin, R. R. (2017) · Journal of Computer Science and Technology · doi:10.1007/s11390-017-1734-y · Cited by 23

Unsupervised Learning-Based Depth Estimation-Aided Visual SLAM Approach

Geng, M., Shang, S., Ding, B., Wang, H., & Zhang, P. (2019) · Circuits Systems and Signal Processing · doi:10.1007/s00034-019-01173-3 · Cited by 23

Disambiguating Monocular Depth Estimation with a Single Transient

Nishimura, M., Lindell, D. B., Metzler, C. A., & Wetzstein, G. (2020) · Lecture notes in computer science · doi:10.1007/978-3-030-58589-1_9 · Cited by 23

Image-Based 3D Modeling via Cheeger Sets

Töppe, E., Oswald, M. R., Cremers, D., & Rother, C. (2011) · Lecture notes in computer science · doi:10.1007/978-3-642-19315-6_5 · Cited by 22

Symmetric piecewise planar object reconstruction from a single image

Xue, T., Liu, J., & Tang, X. (2011) · doi:10.1109/cvpr.2011.5995405 · Cited by 22

Image classification using SLIC superpixel and FAAGKFCM image segmentation

Singh, N. K., Singh, N. J., & Kumar, W. K. (2019) · IET Image Processing · doi:10.1049/iet-ipr.2019.0255 · Cited by 22

Seeing 3D objects in a single 2D image

Rother, D., & Sapiro, G. (2009) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2009.5459405 · Cited by 22

Im2depth: Scalable exemplar based depth transfer

Baig, M. H., Jagadeesh, V., Piramuthu, R., Bhardwaj, A., Di, W., & Sundaresan, N. (2014) · IEEE Winter Conference on Applications of Computer Vision · doi:10.1109/wacv.2014.6836091 · Cited by 21

SUW-Learn: Joint Supervised, Unsupervised, Weakly Supervised Deep Learning for Monocular Depth Estimation

Ren, H., Raj, A., El‐Khamy, M., & Lee, J. (2020) · IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) · doi:10.1109/cvprw50498.2020.00383 · Cited by 21

Surface and contour-preserving origamic architecture paper pop-ups

Le, S. N., Leow, S.-J., Le-Nguyen, T.-V., Ruiz, C. R., Jr., & Low, K. (2013) · IEEE Transactions on Visualization and Computer Graphics · doi:10.1109/tvcg.2013.108 · Cited by 21

RepFinder

Cheng, M., Zhang, F., Mitra, N. J., Huang, X., & Hu, S. (2010) · ACM SIGGRAPH Conference (SIGGRAPH) · doi:10.1145/1833349.1778820 · Cited by 21

Incorporating scene priors to dense monocular mapping

Concha, A., Hussain, W., Montano, L., & Civera, J. (2015) · Autonomous Robots · doi:10.1007/s10514-015-9465-9 · Cited by 20

Dynamic Foreground/Background Extraction from Images and Videos using Random Patches

Lü, L., & Hager, G. D. (2007) · The MIT Press eBooks · doi:10.7551/mitpress/7503.003.0121 · Cited by 20

A two-streamed network for estimating fine-scaled depth maps from single RGB images

Li, J., Yuce, C., Klein, R., & Yao, A. (2019) · Computer Vision and Image Understanding · doi:10.1016/j.cviu.2019.06.002 · Cited by 20

What can we learn about the scene structure from three orthogonal vanishing points in images

Wang, G., Tsui, H.-T., & Wu, Q. (2008) · Pattern Recognition Letters · doi:10.1016/j.patrec.2008.09.001 · Cited by 20

LiDAR inpainting from a single image

Becker, J., Stewart, C. V., & Radke, R. J. (2009) · IEEE International Conference on Computer Vision Workshops · doi:10.1109/iccvw.2009.5457441 · Cited by 20

Automatic construction of 3D models from architectural line drawings

Lee, S., Feng, D. H., & Gooch, B. (2008) · ACM SIGGRAPH Symposium on Interactive 3D Graphics and Games (I3D) · doi:10.1145/1342250.1342269 · Cited by 20

Outdoor Augmented Reality: State of the Art and Issues

Zendjebil, I., Ababsa, F., Didier, J.-Y., Vairon, J., Frauciel, L., Hachet, M., Guitton, P., & Delmont, R. (2008) · HAL · Cited by 20

Fine-Scale Surface Normal Estimation Using a Single NIR Image

Yoon, Y., Choe, G., Kim, N. I., Lee, J., & Kweon, I. S. (2016) · Lecture notes in computer science · doi:10.1007/978-3-319-46487-9_30 · Cited by 19

Learning to Reconstruct 3D Non-Cuboid Room Layout from a Single RGB Image

Yang, C., Zheng, J., Dai, X., Tang, R., Ma, Y., & Yuan, X. (2022) · IEEE Winter Conference on Applications of Computer Vision · doi:10.1109/wacv51458.2022.00031 · Cited by 19

Content-Preserving Warps for 3D Video Stabilization

Liu, F., Gleicher, M. L., Jin, H., & Agarwala, A. (2023) · ACM eBooks · doi:10.1145/3596711.3596778 · Cited by 19

GINA-3D: Learning to Generate Implicit Neural Assets in the Wild

Shen, B., Yan, X., Qi, C. R., Najibi, M., Deng, B., Guibas, L. J., Zhou, Y., & Anguelov, D. (2023) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr52729.2023.00476 · Cited by 23

Hallucinating Stereoscopy from a Single Image

Zeng, Q., Chen, W., Wang, H., Tu, C., Cohen‐Or, D., Lischinski, D., & Chen, B. (2015) · Computer Graphics Forum · doi:10.1111/cgf.12536 · Cited by 19

Evaluating Superpixels in Video: Metrics Beyond Figure-Ground Segmentation

Neubert, P., & Protzel, P. (2013) · British Machine Vision Conference (BMVC) · doi:10.5244/c.27.54 · Cited by 19

Fast superpixels for video analysis

Drucker, F., & MacCormick, J. (2009) · IEEE Workshop on Motion and Video Computing · doi:10.1109/wmvc.2009.5399239 · Cited by 19

Depth Transfer: Depth Extraction from Videos Using Nonparametric Sampling

Karsch, K., Liu, C., & Kang, S. B. (2015) · Springer eBooks · doi:10.1007/978-3-319-23048-1_9 · Cited by 17

Persistent self-supervised learning: From stereo to monocular vision for obstacle avoidance

van Hecke, K. G., de Croon, G., van der Maaten, L., Hennes, D., & Izzo, D. (2018) · International Journal of Micro Air Vehicles · doi:10.1177/1756829318756355 · Cited by 18

Depth Estimation From a Single RGB Image Using Fine-Tuned Generative Adversarial Network

Islam, N. U., & Park, J. (2021) · IEEE Access · doi:10.1109/access.2021.3060435 · Cited by 18

DEPT: Depth Estimation by Parameter Transfer for Single Still Images

Li, X., Qin, H., Wang, Y., Zhang, Y., & Dai, Q. (2015) · Lecture notes in computer science · doi:10.1007/978-3-319-16808-1_4 · Cited by 18

Rephotography Using Image Collections

Lee, K., Luo, S., & Chen, B. (2011) · Computer Graphics Forum · doi:10.1111/j.1467-8659.2011.02042.x · Cited by 18

Sparse2Dense: From Direct Sparse Odometry to Dense 3-D Reconstruction

Tang, J., Folkesson, J. B., & Jensfelt, P. (2019) · IEEE Robotics and Automation Letters · doi:10.1109/lra.2019.2891433 · Cited by 18

Variable grouping for energy minimization

Kim, T., Nowozin, S., Kohli, P., & Yoo, C. D. (2011) · doi:10.1109/cvpr.2011.5995645 · Cited by 17

A Review of Geometry Recovery from a Single Image Focusing on Curved Object Reconstruction

Oswald, M. R., Töppe, E., Nieuwenhuis, C., & Cremers, D. (2012) · Mathematics and visualization · doi:10.1007/978-3-642-34141-0_16 · Cited by 17

Hierarchical Surface Prediction

Häne, C., Tulsiani, S., & Malik, J. (2019) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2019.2896296 · Cited by 17

Monocular Depth Estimation Using Information Exchange Network

Su, W., Zhang, H., Zhou, Q., Yang, W., & Wang, Z. (2020) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2020.3008991 · Cited by 17

Single View Depth Estimation from ExamplesPreprint

Hassner, T., & Basri, R. (2013) · arXiv (Cornell University) · doi:10.48550/arxiv.1304.3915 · Cited by 17

Facade Proposals for Urban Augmented Reality

Fond, A., Berger, M., & Simon, G. (2017) · Proceedings - International Symposium on Mixed and Augmented Reality, ISMAR · doi:10.1109/ismar.2017.20 · Cited by 16

Fast Monocular Depth Estimation via Side Prediction Aggregation with Continuous Spatial Refinement

Wu, J., Ji, R., Wang, Q., Zhang, S., Sun, X., Wang, Y., Xu, M., & Huang, F. (2022) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2021.3140001 · Cited by 16

Geo-semantic segmentation

Ardeshir, S., Collins-Sibley, K. M., & Shah, M. A. (2015) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2015.7298896 · Cited by 16

Photo sundial: Estimating the time of capture in consumer photos

Tsai, T.-H., Jhou, W.-C., Cheng, W.-H., Hu, M., Shen, I., Lim, T., Hua, K., Ghoneim, A., Hossain, M. A., & Hidayati, S. C. (2015) · Neurocomputing · doi:10.1016/j.neucom.2015.11.050 · Cited by 16

Indoor scene modeling from a single image using normal inference and edge features

Liu, M., Guo, Y., & Wang, J. (2017) · The Visual Computer · doi:10.1007/s00371-016-1348-3 · Cited by 16

LA-Net

Zheng, K., Zha, Z.-J., Cao, Y. H., Chen, X., & Wu, F. H. (2018) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/3240508.3240628 · Cited by 16

Layered Interpretation of Street View Images

Liu, M.-Y., Lin, S., Ramalingam, S., & Tuzel, O. (2015) · Robotics: Science and Systems · doi:10.15607/rss.2015.xi.025 · Cited by 16

Automated Brain Tumor Detection Using Discriminative Clustering Based MRI Segmentation

Panda, A., Mishra, T. K., & Phaniharam, V. G. (2018) · Advances in intelligent systems and computing · doi:10.1007/978-981-13-2414-7_12 · Cited by 16

Superpixel Based Automatic Segmentation of Corneal Ulcers from Ocular Staining Images

Deng, L., Huang, H., Yuan, J., & Tang, X. (2018) · IEEE International Conference on Digital Signal Processing (DSP) · doi:10.1109/icdsp.2018.8631795 · Cited by 16

FLIC: Fast Linear Iterative Clustering With Active Search

Zhao, J., Ren, B., Hou, Q., Cheng, M., & Rosin, P. L. (2018) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v32i1.12286 · Cited by 16

Image warps for artistic perspective manipulation

Carroll, R., Agarwala, A., & Agrawala, M. (2010) · ACM SIGGRAPH Conference (SIGGRAPH) · doi:10.1145/1833349.1778864 · Cited by 16

On Visual Realism of Synthesized Imagery

Reinhard, E., Efros, A. A., Kautz, J., & Seidel, H. (2013) · Proceedings of the IEEE · doi:10.1109/jproc.2013.2260711 · Cited by 16

Image visual attention computation and application via the learning of object attributes

Han, J., Wang, D., Shao, L., Qian, X., Cheng, G., & Han, J. (2013) · Machine Vision and Applications · doi:10.1007/s00138-013-0558-1 · Cited by 15

Image-based exploration obstacle avoidance for mobile robot

Wang, Y., Fang, S., Cao, Y., & Sun, H. (2009) · Chinese Control and Decision Conference (CCDC) · doi:10.1109/ccdc.2009.5192583 · Cited by 15

Relative Volume Constraints for Single View 3D Reconstruction

Töppe, E., Nieuwenhuis, C., & Cremers, D. (2013) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2013.30 · Cited by 15

Spindle-Net: CNNs for Monocular Depth Inference with Dilation Kernel Method

He, L., Yu, M., & Wang, G. (2018) · Proceedings - International Conference on Pattern Recognition/Proceedings/International Conference on Pattern Recognition · doi:10.1109/icpr.2018.8546170 · Cited by 15

A Model-Driven Method for Pylon Reconstruction from Oblique UAV Images

Huang, W., Jiang, S., & Jiang, W. (2020) · Sensors · doi:10.3390/s20030824 · Cited by 15

2D to 3D conversion of sports content using panoramas

Schnyder, L., Wang, O., & Smolić, A. (2011) · Proceedings - International Conference on Image Processing · doi:10.1109/icip.2011.6115857 · Cited by 14

Video Depth-from-Defocus

Kim, H., Richardt, C., & Theobalt, C. (2016) · International Conference on 3D Vision (3DV) · doi:10.1109/3dv.2016.46 · Cited by 15

Photo navigator

Hsieh, C.-C., Cheng, W.-H., Chang, C.-H., Chuang, Y., & Wu, J. (2008) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/1459359.1459415 · Cited by 15

SkyFinder

Tao, L., Yuan, L., & Sun, J. Z. (2009) · ACM SIGGRAPH Conference (SIGGRAPH) · doi:10.1145/1576246.1531374 · Cited by 15

An Overview of Perception and Decision-Making in Autonomous Systems in the Era of LearningPreprint

Tang, Y. S., Zhao, C., Wang, J., Zhang, C., Sun, Q., Zheng, W. X., Du, W., Qian, F., & Kurths, J. (2020) · arXiv (Cornell University) · Cited by 15

Enhancing 3D applications using stereoscopic 3D and motion parallax

Li, I. K. Y., Peek, E. M., Wünsche, B. C., & Lutteroth, C. (2012) · Cited by 14

Object Detection Using SURF and Superpixels

Lopez-de-la-Calleja, M., Nagai, T., Attamimi, M., Nakano-Miyatake, M., & Perez-Meana, H. M. (2013) · Journal of Software Engineering and Applications · doi:10.4236/jsea.2013.69061 · Cited by 14

Depth Estimation by Parameter Transfer With a Lightweight Model for Single Still Images

Qin, H., Li, X., Wang, Y., Zhang, Y., & Dai, Q. (2016) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2016.2580438 · Cited by 14

Bayesian depth estimation from monocular natural images

Su, C.-C., Cormack, L. K., & Bovik, A. C. (2017) · Journal of Vision · doi:10.1167/17.5.22 · Cited by 15

Interactive normal reconstruction from a single image

Wu, T.-P., Sun, J. Z., Tang, C., & Shum, H. (2008) · ACM SIGGRAPH Conference and Exhibition on Computer Graphics and Interactive Techniques in Asia (SIGGRAPH Asia) · doi:10.1145/1457515.1409072 · Cited by 14

A systematic review of monocular depth estimation for autonomous driving: Methods and dataset benchmarking

huang, Z., Ali, M. A. H., Nukman, Y., Xu, H., Zhang, S., Chen, H., & AlKhedher, M. A. (2025) · Results in Engineering · doi:10.1016/j.rineng.2025.105359 · Cited by 15

A pooled Object Bank descriptor for image scene classification

Zang, M., Wen, D., Liu, T., Zou, H., & Liu, C. (2017) · Expert Systems with Applications · doi:10.1016/j.eswa.2017.10.057 · Cited by 13

Efficient Depth Propagation for Constructing a Layered Depth Image from a Single Image

Iizuka, S., Endo, Y., Kanamori, Y., Mitani, J., & Fukui, Y. (2014) · Computer Graphics Forum · doi:10.1111/cgf.12496 · Cited by 13

Shape from Angle Regularity

Zaheer, A., Rashid, M., & Khan, S. (2012) · Lecture notes in computer science · doi:10.1007/978-3-642-33783-3_1 · Cited by 13

Seeing the World Behind the Image: Spatial Layout for 3D Scene Understanding

Hoiem, D., Efros, A. A., & Kanade, T. (2007) · Cited by 13

Which Edges Matter?

Bansal, A., Kowdle, A., Parikh, D., Gallagher, A., & Zitnick, L. (2013) · IEEE International Conference on Computer Vision Workshops · doi:10.1109/iccvw.2013.80 · Cited by 13

Homogeneous Superpixels from Random Walks

Perbet, F., & Maki, A. (2011) · Cited by 13

Object Depth Estimation from a Single Image Using Fully Convolutional Neural Network

Afifi, A. J., & Hellwich, O. (2016) · International Conference on Digital Image Computing: Techniques and Applications (DICTA) · doi:10.1109/dicta.2016.7797068 · Cited by 13

Single-View Reconstruction using orthogonal line-pairs

Zaheer, A., Rashid, M., Riaz, M. A., & Khan, S. (2018) · Computer Vision and Image Understanding · doi:10.1016/j.cviu.2017.11.014 · Cited by 13

Spatiotemporal road scene reconstruction using superpixel-based Markov random field

Li, Y., Liu, Y., Zhu, J., Ma, S., Niu, Z., & Guo, R. (2019) · Information Sciences · doi:10.1016/j.ins.2019.08.038 · Cited by 13

Construction of 3D models from single view images: A survey based on various approaches

Mohan, S., & Mani, L. M. (2011) · International Conference on Emerging Trends in Electrical and Computer Technology · doi:10.1109/icetect.2011.5760180 · Cited by 12

Automatic Paper Sliceform Design from 3D Solid Models

Le-Nguyen, T.-V., Low, K., Ruiz, C. R., Jr., & Le, S. N. (2013) · IEEE Transactions on Visualization and Computer Graphics · doi:10.1109/tvcg.2013.82 · Cited by 12

The application of series multi-pooling convolutional neural networks for medical image segmentation

Wang, F., Huang, S., Shi, L., & Fan, W. (2017) · International Journal of Distributed Sensor Networks · doi:10.1177/1550147717748899 · Cited by 12

X-Section: Cross-Section Prediction for Enhanced RGB-D Fusion

Nicastro, A., Clark, R., & Leutenegger, S. (2019) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2019.00160 · Cited by 13

Learning to Produce 3D Media From a Captured 2D Video

Park, M., Luo, J., Gallagher, A., & Rabbani, M. (2013) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2013.2264926 · Cited by 12

Single and sparse view 3D reconstruction by learning shape priors

Chen, Y., & Cipolla, R. (2011) · Computer Vision and Image Understanding · doi:10.1016/j.cviu.2010.10.015 · Cited by 12

A sketch-based interface for photo pop-up

Ventura, J., DiVerdi, S., & Höllerer, T. (2009) · Sketch Based Interfaces and Modeling · doi:10.1145/1572741.1572746 · Cited by 12

On the use of supervised features for unsupervised image categorization: An evaluation

Ciocca, G., Cusano, C., Santini, S., & Schettini, R. (2014) · Computer Vision and Image Understanding · doi:10.1016/j.cviu.2014.01.010 · Cited by 12

Approximating Functions on a Mesh with Restricted Voronoï Diagrams

Nivoliers, V., & Bruno Lévy, B. (2013) · Computer Graphics Forum · doi:10.1111/cgf.12175 · Cited by 12

Learning Fine-Scaled Depth Maps from Single RGB Images.Preprint

Li, J., Klein, R., & Yao, A. (2016) · arXiv (Cornell University) · Cited by 12

Application of Convolutional Neural Networks for Three-Dimensional Reconstruction of the Geometry of Objects in the Image

Gadasin, D. V., Вячеславович, Ш. А., Kuzin, I. A., & Gadasin, D. D. (2022) · Intelligent Technologies and Electronic Devices in Vehicle and Road Transport Complex (TIRVED) · doi:10.1109/tirved56496.2022.9965459 · Cited by 11

Cut-and-Fold: Automatic 3D modeling from a single image

Wang, G., Chen, X., & Chen, S. (2014) · IEEE International Conference on Multimedia and Expo workshops · doi:10.1109/icmew.2014.6890555 · Cited by 3

Automatic generation of 3D models from photographs

Pollefeys, M., Koch, R., Vergauwen, M., & Gool, L. V. (1998) · Cited by 10

Photo-inspired model-driven 3D object modeling

Xu, K., Zheng, H., Zhang, H., Cohen‐Or, D., Liu, L., & Xiong, Y. (2011) · ACM Transactions on Graphics · doi:10.1145/2010324.1964975 · Cited by 71

Multi‐style paper pop‐up designs from 3D models

Ruiz, C. R., Jr., Le, S. N., Yu, J., & Low, K. (2014) · Computer Graphics Forum · doi:10.1111/cgf.12320 · Cited by 29

Multiple Model Photo Popup

Bidwell, J., Decell, J., & Mokszycki, S. (2012)