Monocular depth estimation with hierarchical fusion of dilated CNNs and soft-weighted-sum inference

Deep Residual Learning for Image Recognition

He, K., Zhang, X., Ren, S., & Sun, J. (2016) · 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2016.90 · Cited by 235,474

Very Deep Convolutional Networks for Large-Scale Image Recognition

Simonyan, K., & Zisserman, A. (2014) · arXiv · doi:10.48550/arxiv.1409.1556 · Cited by 114,148

ImageNet classification with deep convolutional neural networks

Krizhevsky, A., Sutskever, I., & Hinton, G. E. (2017) · Communications of the ACM · doi:10.1145/3065386 · Cited by 112,155

DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs

Chen, L.-C., Papandreou, G., Kokkinos, I., Murphy, K., & Yuille, A. L. (2018) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2017.2699184 · Cited by 22,392

Proceedings of IEEE Conference on Computer Vision and Pattern Recognition

(1993) · doi:10.1109/cvpr.1993 · Cited by 17,989

Are we ready for autonomous driving? The KITTI vision benchmark suite

Geiger, A., Lenz, P., & Urtasun, R. (2012) · 2012 IEEE Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2012.6248074 · Cited by 14,897

Proceedings of IEEE International Conference on Computer Vision

(1995) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.1995.466933 · Cited by 13,117

Fully convolutional networks for semantic segmentation

Shelhamer, E., Long, J., & Darrell, T. (2017) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2016.2572683 · Cited by 11,898

Multi-scale context aggregation by dilated convolutions

Yu, F., & Koltun, V. (2015) · arXiv · doi:10.48550/arxiv.1511.07122 · Cited by 7,738

Indoor segmentation and support inference from rgbd images

Silberman, N., Hoiem, D., Kohli, P., & Fergus, R. (2012) · Lecture Notes in Computer Science · doi:10.1007/978-3-642-33715-4_54 · Cited by 5,760

Caffe: Convolutional Architecture for Fast Feature EmbeddingPreprint

Jia, Y., Shelhamer, E., Donahue, J., Karayev, S., Long, J., Girshick, R., Guadarrama, S., & Darrell, T. (2014) · arXiv (Cornell University) · doi:10.48550/arxiv.1408.5093 · Cited by 5,299

Proceedings European Conference on Computer Vision 2002

Heyden, A., Sparr, G., Nielsen, M., & Johansen, P. (2002) · Lund University Publications (Lund University) · Cited by 5,153

Depth Map Prediction from a Single Image using a Multi-Scale Deep Network

Eigen, D., Puhrsch, C., & Fergus, R. (2014) · arXiv · doi:10.48550/arxiv.1406.2283 · Cited by 3,442

Unsupervised Monocular Depth Estimation with Left-Right Consistency

Godard, C., Aodha, O. M., & Brostow, G. J. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2017.699 · Cited by 3,270

Unsupervised Learning of Depth and Ego-Motion from Video

Zhou, T., Brown, M., Snavely, N., & Lowe, D. G. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2017.700 · Cited by 2,910

Predicting Depth, Surface Normals and Semantic Labels with a Common Multi-scale Convolutional Architecture

Eigen, D., & Fergus, R. (2015) · 2015 IEEE International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2015.304 · Cited by 2,862

Deeper Depth Prediction with Fully Convolutional Residual Networks

Laina, I., Rupprecht, C., Belagiannis, V., Tombari, F., & Navab, N. (2016) · International Conference on 3D Vision (3DV) · doi:10.1109/3dv.2016.32 · Cited by 2,105

Make3D: Learning 3D Scene Structure from a Single Still Image

Saxena, A., Sun, M., & Ng, A. Y. (2009) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2008.132 · Cited by 1,749

Shape-from-shading: A survey

Zhang, R., Tsai, P.-S., Cryer, J. E., & Shah, M. (1999) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.784284 · Cited by 1,731

Unsupervised CNN for Single View Depth Estimation: Geometry to the Rescue

Garg, R., BG, V. K., Carneiro, G., & Reid, I. (2016) · arXiv · doi:10.48550/arxiv.1603.04992 · Cited by 1,632

Unsupervised CNN for Single View Depth Estimation: Geometry to the Rescue

Garg, R., B.G., V. K., Carneiro, G., & Reid, I. (2016) · Lecture Notes in Computer Science · doi:10.1007/978-3-319-46484-8_45 · Cited by 1,632

Hypercolumns for object segmentation and fine-grained localization

Hariharan, B., Arbelaez, P., Girshick, R., & Malik, J. (2015) · 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2015.7298642 · Cited by 1,511

Learning Depth from Single Monocular Images Using Deep Convolutional Neural Fields

Liu, F., Shen, C., Lin, G., & Reid, I. D. (2015) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2015.2505283 · Cited by 1,231

DeMoN: Depth and Motion Network for Learning Monocular Stereo

Ummenhofer, B., Zhou, H., Uhrig, J., Mayer, N., Ilg, E., Dosovitskiy, A., & Brox, T. (2017) · 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.2017.596 · Cited by 712

Semi-Supervised Deep Learning for Monocular Depth Map Prediction

Kuznietsov, Y., Stuckler, J., & Leibe, B. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2017.238 · Cited by 680

Depth and surface normal estimation from monocular images using regression on deep features and hierarchical CRFs

Li, B., Shen, C., Dai, Y., van den Hengel, A., & He, M. (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.2015.7298715 · Cited by 621

Single image depth estimation from predicted semantic labels

Liu, B., Gould, S. J., & Koller, D. (2010) · 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.2010.5539823 · Cited by 484

Multi-scale Continuous CRFs as Sequential Deep Networks for Monocular Depth Estimation

Xu, D., Ricci, E., Ouyang, W., Wang, X., & Sebe, N. (2017) · 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.2017.25 · Cited by 484

Estimating Depth From Monocular Images as Classification Using Deep Fully Convolutional Residual Networks

Cao, Y., Wu, Z., & Shen, C. (2017) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2017.2740321 · Cited by 467

Pulling Things out of Perspective

Ladický, Ľ., Shi, J., & Pollefeys, M. (2014) · 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.2014.19 · Cited by 464

Towards unified depth and semantic prediction from a single image

Wang, P., Shen, X., Lin, Z., Cohen, S. D., Price, B. L., & Yuille, 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.2015.7298897 · Cited by 455

Depth Transfer: Depth Extraction from Video Using Non-Parametric Sampling

Karsch, K., Liu, C., & Kang, S. B. (2014) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2014.2316835 · Cited by 453

Single-Image Depth Perception in the WildPreprint

Chen, W., Zhao, F., Yang, D., & Deng, J. (2016) · arXiv (Cornell University) · doi:10.48550/arxiv.1604.03901 · Cited by 418

A survey of human motion analysis using depth imagery

Chen, L., Wei, H., & Ferryman, J. (2013) · Pattern Recognition Letters · doi:10.1016/j.patrec.2013.02.006 · Cited by 400

Robust human activity recognition from depth video using spatiotemporal multi-fused features

Jalal, A., Kim, Y.-H., Kim, Y.-J., Kamal, S., & Kim, D. (2016) · Pattern Recognition · doi:10.1016/j.patcog.2016.08.003 · Cited by 397

Discrete-Continuous Depth Estimation from a Single Image

Liu, M., Salzmann, M., & He, X. (2014) · 2014 IEEE Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2014.97 · Cited by 381

Learning Sensor-Specific Spatial-Spectral Features of Hyperspectral Images via Convolutional Neural Networks

Mei, S., Ji, J., Hou, J., Li, X., & Du, Q. (2017) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2017.2693346 · Cited by 320

Monocular Depth Estimation Using Neural Regression Forest

Roy, A., & Todorović, S. (2016) · 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.2016.594 · Cited by 319

Blocks World Revisited: Image Understanding Using Qualitative Geometry and Mechanics

Gupta, A., Efros, A. A., & Hebert, M. (2010) · Lecture notes in computer science · doi:10.1007/978-3-642-15561-1_35 · Cited by 310

Unsupervised Learning of Depth and Ego-Motion from VideoPreprint

Zhou, T., Brown, M., Snavely, N., et al. (2017) · arXiv (Cornell University) · doi:10.48550/arxiv.1704.07813 · Cited by 217

Unfolding an Indoor Origami World

Fouhey, D. F., Gupta, A., & Hebert, M. (2014) · Lecture notes in computer science · doi:10.1007/978-3-319-10599-4_44 · Cited by 85

Repetition-based dense single-view reconstruction

Wu, C., Frahm, J., & Pollefeys, M. (2011) · 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.2011.5995551 · Cited by 76

Semi-Supervised Deep Learning for Monocular Depth Map PredictionPreprint

Kuznietsov, Y., Stückler, J., & Leibe, B. (2017) · arXiv (Cornell University) · doi:10.48550/arxiv.1702.02706 · Cited by 66

Depth from Defocus Estimation in Spatial Domain

Ziou, D., & Deschênes, F. (2001) · Computer Vision and Image Understanding · doi:10.1006/cviu.2000.0899 · Cited by 62

Multi-Scale Continuous CRFs as Sequential Deep Networks for Monocular Depth EstimationPreprint

Xu, D., Ricci, E., Ouyang, W., et al. (2017) · arXiv (Cornell University) · doi:10.48550/arxiv.1704.02157 · Cited by 42

Hierarchically Supervised Deconvolutional Network for Semantic Video Segmentation

Wang, Y., Liu, J., Li, Y., Fu, J., Xu, M. G., & Lu, H. (2016) · Pattern Recognition · doi:10.1016/j.patcog.2016.09.046 · Cited by 34

Joint Depth and Semantic Inference from a Single Image via Elastic Conditional Random Field

Ji, R., Cao, L., & Wang, Y. (2016) · Pattern Recognition · doi:10.1016/j.patcog.2016.03.016 · Cited by 13

Feature representation of RGB-D images using joint spatial-depth feature pooling

Pan, H., Olsen, S. I., & Zhu, Y. (2016) · Pattern Recognition Letters · doi:10.1016/j.patrec.2016.04.001 · Cited by 2

Digging Into Self-Supervised Monocular Depth Estimation

Godard, C., Aodha, O. M., Firman, M., & Brostow, G. (2019) · 2019 IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2019.00393 · Cited by 2,561

PAD-Net: Multi-tasks Guided Prediction-and-Distillation Network for Simultaneous Depth Estimation and Scene Parsing

Xu, D., Ouyang, W., Wang, X., & Sebe, N. (2018) · 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.2018.00077 · Cited by 551

Monocular human pose estimation: A survey of deep learning-based methods

Chen, Y., Tian, Y., & He, M. (2020) · Computer Vision and Image Understanding · doi:10.1016/j.cviu.2019.102897 · Cited by 479

Very high resolution canopy height maps from RGB imagery using self-supervised vision transformer and convolutional decoder trained on aerial lidar

Tolan, J., Yang, H.-I., Nosarzewski, B., Couairon, G., Vo, H. V., Brandt, J., Spore, J., Majumdar, S., Haziza, D., Vamaraju, J., et al. (2024) · Remote Sensing of Environment · doi:10.1016/j.rse.2023.113888 · Cited by 419

Structured Attention Guided Convolutional Neural Fields for Monocular Depth Estimation

Xu, D., Wang, W., Tang, H., Liu, H., Sebe, N., & Ricci, E. (2018) · 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.2018.00412 · Cited by 358

Monocular Depth Estimation Using Multi Scale Neural Network And Feature FusionPreprint

Sagar, A. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2009.09934 · Cited by 2

Monocular Depth Estimation Based on Dilated Convolutions and Feature Fusion

Li, H., Liu, S., Wang, B., & Wu, Y. (2024) · Applied Sciences · doi:10.3390/app14135833 · Cited by 1

Depth Estimation from Monocular Images Using Dilated Convolution and Uncertainty Learning

Ma, H., Ding, Y., Wang, L., Zhang, M., & Li, D. (2018) · Lecture notes in computer science · doi:10.1007/978-3-030-00767-6_2 · Cited by 2

Monocular Depth Estimation Based on Multi-Scale Depth Map Fusion

Xin, Y., Chang, Q., Liu, X., He, S., & Cui, Y. (2021) · IEEE Access · doi:10.1109/access.2021.3076346 · Cited by 15

Deep Classification Network for Monocular Depth EstimationPreprint

Azeez, O., Zou, Y., & Kumar, B. V. K. V. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1910.10369 · Cited by 1