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We present Mix3D, a data augmentation technique for segmenting large-scale 3D scenes.
Perceiving Real-World Scenes
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Contextual Relations: The Influence of Familiarity, Physical Plausibility, and Belongingness
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Vicinal Risk Minimization
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Efficient Graph-based Image Segmentation
P. F. Felzenszwalb and D. P. Huttenlocher · 2004
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The Role of Context in Object Recognition
A. Oliva and A. Torralba · 2007
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Microsoft COCO: Common Objects in Context
T.-Y. Lin, M. Maire, S. Belongie, J. Hays, P. Perona, D. Ramanan, P. Dollar, and L. Zitnick · 2014
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Dropout: A Simple Way to Prevent Neural Networks From Overfitting
N. Srivastava, G. E. Hinton, A. Krizhevsky, I. Sutskever, and R. Salakhutdinov · 2014
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U-Net: Convolutional Networks for Biomedical Image Segmentation
O. Ronneberger, P. Fischer, and T. Brox · 2015
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3D Semantic Parsing of Large-Scale Indoor Spaces
I. Armeni, O. Sener, A. R. Zamir, H. Jiang, I. Brilakis, M. Fischer, and S. Savarese · 2016
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Deep Learning
I. Goodfellow, Y. Bengio, and A. Courville · 2016
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ScanNet: Richly-annotated 3D Reconstructions of Indoor Scenes
A. Dai, A. X. Chang, M. Savva, M. Halber, T. Funkhouser, and M. Nießner · 2017
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Improved Regularization of Convolutional Neural Networks with Cutout
T. DeVries and G. W. Taylor · 2017
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Cut, Paste and Learn: Surprisingly Easy Synthesis for Instance Detection
D. Dwibedi, I. Misra, and M. Hebert · 2017
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Exploring Spatial Context for 3D Semantic Segmentation of Point Clouds
F. Engelmann, T. Kontogianni, A. Hermans, and B. Leibe · 2017
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PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
C. R. Qi, H. Su, K. Mo, and L. J. Guibas · 2017
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PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space
C. R. Qi, L. Yi, H. Su, and L. J. Guibas · 2017
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SEGCloud: Semantic Segmentation of 3D Point Clouds
L. P. Tchapmi, C. B. Choy, I. Armeni, J. Gwak, and S. Savarese · 2017
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O-CNN: Octree-based Convolutional Neural Networks for 3D Shape Analysis
P.-S. Wang, Y. Liu, Y.-X. Guo, C.-Y. Sun, and X. Tong · 2017
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Augmented Reality Meets Computer Vision: Efficient Data Generation for Urban Driving Scenes
H. Alhaija, S. Mustikovela, L. Mescheder, A. Geiger, and C. Rother · 2018
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Modeling Visual Context is Key to Augmenting Object Detection Datasets
N. Dvornik, J. Mairal, and C. Schmid · 2018
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3D Semantic Segmentation with Submanifold Sparse Convolutional Networks
B. Graham, M. Engelcke, and L. van der Maaten · 2018
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Recurrent Slice Networks for 3D Segmentation of Point Clouds
Q. Huang, W. Wang, and U. Neumann · 2018
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PointCNN: Convolution On X-Transformed Points
Y. Li, R. Bu, M. Sun, W. Wu, X. Di, and B. Chen · 2018
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A. Rosenfeld, R. Zemel, and J. K. Tsotsos · 2018
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Hide-and-Seek: A Data Augmentation Technique for Weakly-Supervised Localization and Beyond
K. K. Singh, H. Yu, A. Sarmasi, G. Pradeep, and Y. Lee · 2018
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Deep Parametric Continuous Convolutional Neural Networks
S. Wang, S. Suo, W. Ma, A. Pokrovsky, and R. Urtasun · 2018
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SECOND: Sparsely Embedded Convolutional Detection
OccuSeg: Occupancy-aware 3D Instance Segmentation
L. Han, T. Zheng, L. Xu, and L. Fang · 2020
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JSENet: Joint Semantic Segmentation and Edge Detection Network for 3D Point Clouds
Z. Hu, M. Zhen, X. Bai, H. Fu, and C.-l. Tai · 2020
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Puzzle Mix: Exploiting Saliency and Local Statistics for Optimal Mixup
J.-H. Kim, W. Choo, and H. O. Song · 2020
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Virtual Multi-view Fusion for 3D Semantic Segmentation
A. Kundu, X. Yin, A. Fathi, D. Ross, B. Brewington, T. Funkhouser, and C. Pantofaru · 2020
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CoReNet: Coherent 3D Scene Reconstruction from a Single RGB Image
S. Popov, P. Bauszat, and V. Ferrari · 2020
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DOPS: Learning to Detect 3D Objects and Predict Their 3D Shapes
D. A. R. Ross, G. L. Lai, Z. L. Lu, A. K. Kundu, A. F. Fathi, T. F. Funkhouser, C. P. Pantofaru, M. N. Najibi, L. S. D. Davis, and V. R. Rathod · 2020
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Y. Yan, Y. Mao, and B. Li · 2018
Cited alongside, same era.
3D Recurrent Neural Networks with Context Fusion for Point Cloud Semantic Segmentation
X. Ye, J. Li, H. Huang, L. Du, and X. Zhang · 2018
Cited alongside, same era.
mixup: Beyond Empirical Risk Minimization
H. Zhang, M. Cisse, Y. N. Dauphin, and D. Lopez-Paz · 2018
Cited alongside, same era.
SemanticKITTI: A Dataset for Semantic Scene Understanding of LiDAR Sequences
J. Behley, M. Garbade, A. Milioto, J. Quenzel, S. Behnke, C. Stachniss, and J. Gall · 2019
Cited alongside, same era.
4D Spatio-Temporal ConvNets: Minkowski Convolutional Neural Networks
C. Choy, J. Y. Gwak, and S. Savarese · 2019
Cited alongside, same era.
MixUp as Locally Linear Out-of-Manifold Regularization
H. Guo, Y. Mao, and R. Zhang · 2019
Cited alongside, same era.
Not Using the Car to See the Sidewalk Quantifying and Controlling the Effects of Context in Classification and Segmentation
R. Shetty, B. Schiele, and M. Fritz · 2019
Cited alongside, same era.
Later among the works it cites.
DualConvMesh-Net: Joint Geodesic and Euclidean Convolutions on 3D Meshes
J. Schult*, F. Engelmann*, T. Kontogianni, and B. Leibe · 2020
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D. Walawalkar, Z. Shen, Z. Liu, and M. Savvides · 2020
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PointASNL: Robust Point Clouds Processing Using Nonlocal Neural Networks with Adaptive Sampling
X. Yan, C. Zheng, Z. Li, S. Wang, and S. Cui · 2020
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Deep Fusionnet for Point Cloud Semantic Segmentation
F. Zhang, J. Fang, B. Wah, and P. Torr · 2020
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Learning Object Placement by Inpainting for Compositional Data Augmentation
L. Zhang, T. Wen, J. Min, J. Wang, D. Han, and J. Shi · 2020
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Random Erasing Data Augmentation
Z. Zhong, L. Zheng, G. Kang, S. Li, and Y. Yang · 2020
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Self-Supervised Learning for Domain Adaptation on Point Clouds
I. Achituve, H. Maron, and G. Chechik · 2021
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From Points to Multi-Object 3D Reconstruction
F. Engelmann, K. Rematas, B. Leibe, and V. Ferrari · 2021
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Omni-supervised Point Cloud Segmentation via Gradual Receptive Field Component Reasoning
J. Gong, J. Xu, X. Tan, H. Song, Y. Qu, Y. Xie, and L. Ma · 2021
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Bidirectional Projection Network for Cross Dimension Scene Understanding
W. Hu, H. Zhao, L. Jiang, J. Jia, and T.-T. Wong · 2021
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VMNet: Voxel-Mesh Network for Geodesic-Aware 3D Semantic Segmentation
Z. Hu, X. Bai, J. Shang, R. Zhang, J. Dong, X. Wang, G. Sun, H. Fu, and C.-L. Tai · 2021
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Regularization Strategy for Point Cloud via Rigidly Mixed Sample
D. Lee, J. Lee, J. Lee, H. Lee, M. Lee, S. Woo, and S. Lee · 2021
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One Thing One Click: A Self-Training Approach for Weakly Supervised 3D Semantic Segmentation
Z. Liu, X. Qi, and C.-W. Fu · 2021
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SaliencyMix: A Saliency Guided Data Augmentation Strategy for Better Regularization
A. F. M. S. Uddin, M. S. Monira, W. Shin, T. Chung, and S.-H. Bae · 2021
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PointCutMix: Regularization Strategy for Point Cloud Classification
J. Zhang, L. Chen, B. Ouyang, B. Liu, J. Zhu, Y. Chen, Y. Meng, and D. Wu · 2021
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