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1708.01642
Cited By
Cut, Paste and Learn: Surprisingly Easy Synthesis for Instance Detection
4 August 2017
Debidatta Dwibedi
Ishan Misra
M. Hebert
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Papers citing
"Cut, Paste and Learn: Surprisingly Easy Synthesis for Instance Detection"
50 / 274 papers shown
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Yoshiaki Bando
Kohei Yatabe
Y. Sasaki
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Yasuhiro Oikawa
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176
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On Robustness and Transferability of Convolutional Neural Networks
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Jessica Yung
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16 Jul 2020
ClassMix: Segmentation-Based Data Augmentation for Semi-Supervised Learning
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Viktor Olsson
Wilhelm Tranheden
Juliano Pinto
Lennart Svensson
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Towards Realistic 3D Embedding via View Alignment
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Danielle M. Cholewiak
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Zizhao Zhang
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449
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Distilling Localization for Self-Supervised Representation Learning
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Self6D: Self-Supervised Monocular 6D Object Pose Estimation
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Fabian Manhardt
Jianzhun Shao
Xiangyang Ji
Nassir Navab
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255
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WQT and DG-YOLO: towards domain generalization in underwater object detection
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Runwei Ding
126
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Improving 3D Object Detection through Progressive Population Based Augmentation
European Conference on Computer Vision (ECCV), 2020
Shuyang Cheng
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Quoc V. Le
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Daniel Ward
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302
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Mixup Regularization for Region Proposal based Object Detectors
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Fabrizio Bottarel
Giulia Vezzani
Ugo Pattacini
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151
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12 Feb 2020
Saliency Driven Perceptual Image Compression
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Srikar Appalaraju
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Learning Object Placements For Relational Instructions by Hallucinating Scene Representations
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Oier Mees
Alp Emek
Johan Vertens
Wolfram Burgard
277
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23 Jan 2020
Instance Segmentation of Visible and Occluded Regions for Finding and Picking Target from a Pile of Objects
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Kentaro Wada
Shingo Kitagawa
K. Okada
Masayuki Inaba
ISeg
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126
26
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21 Jan 2020
The benefits of synthetic data for action categorization
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Mohamad Ballout
Mohammad Tuqan
Daniel C. Asmar
Elie A. Shammas
George E. Sakr
79
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20 Jan 2020
Combining Deep Learning and Verification for Precise Object Instance Detection
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309
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Metamorphic Testing for Object Detection Systems
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157
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Data Augmentation Using Adversarial Training for Construction-Equipment Classification
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Deep Template-based Object Instance Detection
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Mathieu Garon
Philippe Giguère
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137
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Yinlin Hu
Pascal Fua
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RGB-D Individual Segmentation
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Yanjun Fu
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125
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346
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Conditional Transferring Features: Scaling GANs to Thousands of Classes with 30% Less High-quality Data for Training
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Human Synthesis and Scene Compositing
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M. Zanfir
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Imbalance Problems in Object Detection: A Review
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Baris Can Cam
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Synthetic patches, real images: screening for centrosome aberrations in EM images of human cancer cells
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I. Haberbosch
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InstaBoost: Boosting Instance Segmentation via Probability Map Guided Copy-Pasting
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