Fetching the paper…
Reading the bibliography…
Deep learning-solutions for hand-object 3D pose and shape estimation are now very effective when an annotated dataset is available to train them to handle the scenarios and lighting conditions they will encounter at test time.
J. Hoffman, E. Tzeng, T. Park, J. Zhu, P. Isola, K. Saenko, A. Efros, and T. Darrell, “CyCADA: Cycle Consistent Adversarial Domain Adaptation,” in International Conference on Machine Learning , 2018, pp. 1989–1998
1998
Earlier work this paper cites.
A. Miller and P. Allen, “Graspit! a Versatile Simulator for Robotic Grasping,” IEEE Robotics & Automation Magazine , vol. 11, no. 4, pp. 110–122, 2004
2004
Earlier work this paper cites.
A. Gretton, K. Borgwardt, M. Rasch, B. Schölkopf, and A. Smola, “A Kernel Method for the Two-Sample Problem,” in Advances in Neural Information Processing Systems , 2007, pp. 513–520
2007
Earlier work this paper cites.
H. Hamer, K. Schindler, E. Koller-Meier, and L. V. Gool, “Tracking a Hand Manipulating an Object,” in International Conference on Computer Vision , 2009, pp. 1475–1482
2009
Earlier work this paper cites.
J. Deng, W. Dong, R. Socher, L.-J. Li, K. Li, and L. Fei-Fei, “Imagenet: A Large-Scale Hierarchical Image Database,” in Conference on Computer Vision and Pattern Recognition , 2009
2009
Earlier work this paper cites.
H. Hamer, J. Gall, T. Weise, and L. V. Gool, “An Object-Dependent Hand Pose Prior from Sparse Training Data,” in Conference on Computer Vision and Pattern Recognition , 2010, pp. 671–678
2010
Earlier work this paper cites.
J. Romero, H. Kjellström, and D. Kragic, “Hands in Action: Real-Time 3D Reconstruction of Hands in Interaction with Objects,” in International Conference on Robotics and Automation , 2010, pp. 458–463
2010
Earlier work this paper cites.
L. Ballan, A. Taneja, J. Gall, L. V. Gool, and M. Pollefeys, “Motion Capture of Hands in Action Using Discriminative Salient Points,” in European Conference on Computer Vision , 2012, pp. 640–653
2012
Earlier work this paper cites.
I. Oikonomidis, N. Kyriazis, and A. Argyros, “Tracking the Articulated Motion of Two Strongly Interacting Hands,” in Conference on Computer Vision and Pattern Recognition , 2012, pp. 1862–1869
2012
Earlier work this paper cites.
E. Tzeng, J. Hoffman, N. Zhang, K. Saenko, and T. Darrell, “Deep Domain Confusion: Maximizing for Domain Invariance,” in arXiv Preprint , 2014
2014
Earlier work this paper cites.
I. Goodfellow, J. Pouget-Abadie, M. Mirza, B. Xu, D. Warde-Farley, S. Ozair, A. Courville, and Y. Bengio, “Generative Adversarial Nets,” in Advances in Neural Information Processing Systems , 2014, pp. 2672–2680
2014
Earlier work this paper cites.
Y. Ganin and V. Lempitsky, “Unsupervised Domain Adaptation by Backpropagation,” in International Conference on Machine Learning , 2015, pp. 1180–1189
2015
Earlier work this paper cites.
M. Long, Y. Cao, J. Wang, and M. I. Jordan, “Learning Transferable Features with Deep Adaptation Networks,” in International Conference on Machine Learning , 2015, pp. 97–105
2015
Earlier work this paper cites.
D. Tzionas and J. Gall, “3D Object Reconstruction from Hand-Object Interactions,” in International Conference on Computer Vision , 2015, pp. 729–737
2015
Earlier work this paper cites.
G. Rogez, J. Supancic, and D. Ramanan, “Understanding Everyday Hands in Action from RGB-D Images,” in International Conference on Computer Vision , 2015, pp. 3889–3897
2015
Earlier work this paper cites.
G. Rogez, J. Supancic, and D. Ramanan, “First-Person Pose Recognition Using Egocentric Workspaces,” in Conference on Computer Vision and Pattern Recognition , 2015, pp. 4325–4333
2015
Earlier work this paper cites.
E. Tzeng, J. Hoffman, T. Darrell, and K. Saenko, “Simultaneous Deep Transfer Across Domains and Tasks,” in International Conference on Computer Vision , 2015, pp. 4068–4076
2015
Earlier work this paper cites.
C. Doersch, A. Gupta, and A. Efros, “Unsupervised Visual Representation Learning by Context Prediction,” in International Conference on Computer Vision , 2015, pp. 1422–1430
2015
Earlier work this paper cites.
X. Shi, Z. Chen, H. Wang, D. Yeung, W. Wong, and W. Woo, “Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting,” in Advances in Neural Information Processing Systems , 2015, pp. 802–810
2015
Earlier work this paper cites.
D. P. Kingma and J. Ba, “Adam: A Method for Stochastic Optimisation,” in International Conference on Learning Representations , 2015
2015
Earlier work this paper cites.
A. Chang, T. Funkhouser, L. G., P. Hanrahan, Q. Huang, Z. Li, S. Savarese, M. Savva, S. Song, H. Su, J. Xiao, L. Yi, and F. Yu, “Shapenet: An Information-Rich 3D Model Repository,” in arXiv Preprint , 2015
2015
Earlier work this paper cites.
F. Yu, A. Seff, Y. Zhang, S. Song, T. Funkhouser, and J. Xiao, “Lsun: Construction of a Large-Scale Image Dataset Using Deep Learning with Humans in the Loop,” in arXiv Preprint , 2015
2015
Earlier work this paper cites.
M. Long, H. Zhu, J. Wang, and M. Jordan, “Unsupervised domain adaptation with residual transfer networks,” in Advances in Neural Information Processing Systems , 2016, pp. 136–144
2016
Earlier work this paper cites.
W. Zellinger, T. Grubinger, E. Lughofer, T. Natschläger, and S. Saminger-Platz, “Central Moment Discrepancy (cmd) for Domain-Invariant Representation Learning,” in International Conference on Learning Representations , 2016
2016
Earlier work this paper cites.
S. Sridhar, F. Mueller, M. Zollhöfer, D. Casas, A. Oulasvirta, and C. Theobalt, “Real-Time Joint Tracking of a Hand Manipulating an Object from RGB-D Input,” in European Conference on Computer Vision , 2016, pp. 294–310
2016
Earlier work this paper cites.
D. Tzionas, L. Ballan, A. Srikantha, P. Aponte, M. Pollefeys, and J. Gall, “Capturing Hands in Action Using Discriminative Salient Points and Physics Simulation,” International Journal of Computer Vision , vol. 118, no. 2, pp. 172–193, 2016
2016
Earlier work this paper cites.
B. Sun and K. Saenko, “Deep CORAL: Correlation Alignment for Deep Domain Adaptation,” in European Conference on Computer Vision , 2016, pp. 443–450
2016
Earlier work this paper cites.
Y. Ganin, E. Ustinova, H. Ajakan, P. Germain, H. Larochelle, F. Laviolette, M. Marchand, and V. S. Lempitsky, “Domain-Adversarial Training of Neural Networks,” Journal of Machine Learning Research , vol. 17, pp. 591–5935, 2016
2016
Earlier work this paper cites.
R. R. Zhang, P. P. Isola, and A. A. A. Efros, “Colorful Image Colorization,” in European Conference on Computer Vision , 2016, pp. 649–666
2016
Earlier work this paper cites.
G. Larsson, M. Maire, and G. Shakhnarovich, “Learning Representations for Automatic Colorization,” in European Conference on Computer Vision , 2016, pp. 577–593
2016
Earlier work this paper cites.
M. Noroozi and P. Favaro, “Unsupervised Learning of Visual Representations by Solving Jigsaw Puzzles,” in European Conference on Computer Vision , 2016, pp. 69–84
2016
Earlier work this paper cites.
D. Pathak, P. Krähenbühl, J. Donahue, T. Darrell, and A. A. Efros, “Context Encoders: Feature Learning by Inpainting,” in Conference on Computer Vision and Pattern Recognition , 2016
2016
Earlier work this paper cites.
I. Misra, C. Zitnick, and M. Hebert, “Shuffle and learn: unsupervised learning using temporal order verification,” in European Conference on Computer Vision , 2016, pp. 527–544
2016
Earlier work this paper cites.
K. He, X. Zhang, S. Ren, and J. Sun, “Deep Residual Learning for Image Recognition,” in Conference on Computer Vision and Pattern Recognition , 2016, pp. 770–778
2016
Earlier work this paper cites.
Y. Hu, R. Song, and Y. Li, “Efficient Coarse-To-Fine Patch Match for Large Displacement Optical Flow,” in Conference on Computer Vision and Pattern Recognition , 2016
2016
Cited alongside, same era.
T. Simon, H. Joo, I. Matthews, and Y. Sheikh, “Hand Keypoint Detection in Single Images Using Multiview Bootstrapping,” in Conference on Computer Vision and Pattern Recognition , 2017, pp. 1145–1153
2017
Cited alongside, same era.
C. Zimmermann and T. Brox, “Learning to Estimate 3D Hand Pose from Single RGB Images,” in International Conference on Computer Vision , 2017, pp. 4903–4911
2017
Cited alongside, same era.
G. Csurka, “A Comprehensive Survey on Domain Adaptation for Visual Applications,” in Domain Adaptation in Computer Vision Applications . Springer, 2017, pp. 1–35
2017
Cited alongside, same era.
C. C. Vondrick, A. A. Shrivastava, A. A. Fathi, S. S. Guadarrama, and K. K. Murphy, “Tracking Emerges by Colorizing Videos,” in European Conference on Computer Vision , 2018, pp. 391–408
2018
Later among the works it cites.
S. Gidaris, P. Singh, and N. Komodakis, “Unsupervised Representation Learning by Predicting Image Rotations,” in arXiv Preprint , 2018
2018
Later among the works it cites.
T. Groueix, M. Fisher, V. Kim, B. Russell, and M. Aubry, “Atlasnet: A Papier-Mâché Approach to Learning 3D Surface Generation,” in Conference on Computer Vision and Pattern Recognition , 2018
2018
Later among the works it cites.
Y. Wang, Y. Yang, Z. Yang, L. Zhao, P. Wang, and W. Xu, “Occlusion aware unsupervised learning of optical flow,” in Conference on Computer Vision and Pattern Recognition , 2018
2018
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
2017
Cited alongside, same era.
P. Koniusz, Y. Tas, and F. Porikli, “Domain Adaptation by Mixture of Alignments of Second- or Higher-Order Scatter Tensors,” in Conference on Computer Vision and Pattern Recognition , 2017, pp. 4478–4487
2017
Cited alongside, same era.
J.-Y. Zhu, T. Park, P. Isola, and A. Efros, “Unpaired Image-To-Image Translation Using Cycle-Consistent Adversarial Networks,” in International Conference on Computer Vision , 2017, pp. 2223–2232
2017
Cited alongside, same era.
T. Pham, N. Kyriazis, A. Argyros, and A. Kheddar, “Hand-Object Contact Force Estimation from Markerless Visual Tracking,” IEEE Transactions on Pattern Analysis and Machine Intelligence , vol. 40, no. 12, pp. 2883–2896, 2017
2017
Cited alongside, same era.
P. Koniusz, F. Yan, P.-H. Gosselin, and A. K. Mikolajczyk, “Higher-Order Occurrence Pooling for Bags-Of-Words: Visual Concept Detection,” IEEE Transactions on Pattern Analysis and Machine Intelligence , vol. 39, no. 2, pp. 313–326, 2017
2017
Cited alongside, same era.
B. Sun, J. Feng, and K. Saenko, “Correlation Alignment for Unsupervised Domain Adaptation,” in Domain Adaptation in Computer Vision Applications. , 2017, pp. 153–171
2017
Cited alongside, same era.
H. Yan, Y. Ding, P. Li, Q. Wang, Y. Xu, and W. Zuo, “Mind the Class Weight Bias: Weighted Maximum Mean Discrepancy for Unsupervised Domain Adaptation,” in Conference on Computer Vision and Pattern Recognition , 2017, pp. 2272–2281
2017
Cited alongside, same era.
P. Häusser, T. Frerix, A. Mordvintsev, and D. Cremers, “Associative Domain Adaptation,” in International Conference on Computer Vision , 2017, pp. 2784–2792
2017
Cited alongside, same era.
2018
Later among the works it cites.
G. Garcia-Hernando, S. Yuan, S. Baek, and T. Kim, “First-Person Hand Action Benchmark with RGB-D Videos and 3D Hand Pose Annotations,” in Conference on Computer Vision and Pattern Recognition , 2018, pp. 409–419
2018
Later among the works it cites.
Y. Hasson, G. Varol, D. Tzionas, I. Kalevatykh, M. Black, I. Laptev, and C. Schmid, “Learning Joint Reconstruction of Hands and Manipulated Objects,” in Conference on Computer Vision and Pattern Recognition , 2019, pp. 11 807–11 816
2019
Later among the works it cites.
A. Rozantsev, M. Salzmann, and P. Fua, “Beyond Sharing Weights for Deep Domain Adaptation,” IEEE Transactions on Pattern Analysis and Machine Intelligence , vol. 41, no. 4, pp. 801–814, 2019
2019
Later among the works it cites.
M. Qi, W. Li, Z. Yang, Y. Wang, and J. Luo, “Attentive relational networks for mapping images to scene graphs,” in Conference on Computer Vision and Pattern Recognition , 2019
2019
Later among the works it cites.
M. Qi, Y. Wang, J. Qin, and A. Li, “KE-GAN: Knowledge embedded generative adversarial networks for semi-supervised scene parsing,” in Conference on Computer Vision and Pattern Recognition , 2019
2019
Later among the works it cites.
C. Wan, T. Probst, L. V. Gool, and A. Yao, “Self-Supervised 3D Hand Pose Estimation Through Training by Fitting,” in Conference on Computer Vision and Pattern Recognition , 2019
2019
Later among the works it cites.
B. Tekin, F. Bogo, and M. Pollefeys, “H+o: Unified Egocentric Recognition of 3D Hand-Object Poses and Interactions,” in Conference on Computer Vision and Pattern Recognition , 2019, pp. 4511–4520
2019
Later among the works it cites.
T. Vu, H. Jain, M. Bucher, M. Cord, and P. Pérez, “Advent: Adversarial Entropy Minimization for Domain Adaptation in Semantic Segmentation,” in Conference on Computer Vision and Pattern Recognition , 2019, pp. 2517–2526
2019
Later among the works it cites.
Y. Li, L. Yuan, and N. Vasconcelos, “Bidirectional Learning for Domain Adaptation of Semantic Segmentation,” in Conference on Computer Vision and Pattern Recognition , 2019, pp. 6936–6945
2019
Later among the works it cites.
J. Su, Y. Tsai, K. Sohn, B. Liu, S. Maji, and M. Chandraker, “Active Adversarial Domain Adaptation,” in Conference on Computer Vision and Pattern Recognition , 2019
2019
Later among the works it cites.
X. Zhai, A. Oliver, A. Kolesnikov, and L. Beyer, “S4l: Self-Supervised Semi-Supervised Learning,” in International Conference on Computer Vision , 2019, pp. 1476–1485
2019
Later among the works it cites.
V. Sterzentsenko, L. Saroglou, A. Chatzitofis, S. Thermos, N. Zioulis, A. Doumanoglou, D. Zarpalas, and P. Daras, “Self-Supervised Deep Depth Denoising,” in International Conference on Computer Vision , 2019, pp. 1242–1251
2019
Later among the works it cites.
J. Watson, M. Firman, G. Brostow, and D. Turmukhambetov, “Self-Supervised Monocular Depth Hints,” in International Conference on Computer Vision , 2019, pp. 2162–2171
2019
Later among the works it cites.
Z. Feng, C. Xu, and D. Tao, “Self-Supervised Representation Learning from Multi-Domain Data,” in International Conference on Computer Vision , 2019, pp. 3245–3255
2019
Later among the works it cites.
M. Larsson, E. Stenborg, C. Toft, L. Hammarstrand, T. Sattler, and F. Kahl, “Fine-Grained Segmentation Networks: Self-Supervised Segmentation for Improved Long-Term Visual Localization,” in International Conference on Computer Vision , 2019, pp. 31–41
2019
Later among the works it cites.
2019
Later among the works it cites.
Y. Hasson, B. Tekin, F. Bogo, I. Laptev, M. Pollefeys, and C. Schmid, “Leveraging photometric consistency over time for sparsely supervised hand-object reconstruction,” in Conference on Computer Vision and Pattern Recognition , 2020
2020
Closest in time.
R. Bermúdez-Chacón, M. Salzmann, and P. Fua, “Domain Adaptive Multibranch Networks,” in International Conference on Learning Representations , 2020
2020
Closest in time.
M. Qi, Y. Wang, A. Li, and J. Luo, “STC-GAN: Spatio-Temporally Coupled Generative Adversarial Networks for Predictive Scene Parsing,” IEEE Transactions on Image Processing , vol. 29, pp. 5420–5430, 2020
2020
Closest in time.
M. Qi, J. Qin, X. Zhen, D. Huang, Y. Yang, and J. Luo, “Few-Shot Ensemble Learning for Video Classification with SlowFast Memory Networks,” in ACM International Conference on Multimedia , 2020
2020
Closest in time.
M. Qi, J. Qin, Y. Wu, and Y. Yang, “Imitative Non-Autoregressive Modeling for Trajectory Forecasting and Imputation,” in Conference on Computer Vision and Pattern Recognition , 2020
2020
Closest in time.
C. Wan, T. Probst, L. V. Gool, and A. Yao, “Dual Grid Net: Hand Mesh Vertex Regression from Single Depth Maps,” in European Conference on Computer Vision , 2020
2020
Closest in time.
A. Armagan, G. Garcia-Hernando, S. Baek, and et al., “Measuring Generalisation to Unseen Viewpoints, Articulations, Shapes and Objects for 3D Hand Pose Estimation under Hand-Object Interaction,” in European Conference on Computer Vision , 2020
2020
Closest in time.
S. Brahmbhatt, C. Tang, C. Twigg, C. Kemp, and J. Hays, “ContactPose: A Dataset of Grasps with Object Contact and Hand Pose,” in European Conference on Computer Vision , 2020
2020
Closest in time.
S. Hampali, M. Rad, M. Oberweger, and V. Lepetit, “Honnotate: A Method for 3D Annotation of Hand and Object Poses,” in Conference on Computer Vision and Pattern Recognition , 2020
2020
Closest in time.
B. Doosti, S. Naha, M. Mirbagheri, and D. Crandall, “HOPE-Net: A Graph-based Model for Hand-Object Pose Estimation,” in Conference on Computer Vision and Pattern Recognition , 2020
2020
Closest in time.
Y. Yang and S. Soatto, “Fda: Fourier domain adaptation for semantic segmentation,” in Conference on Computer Vision and Pattern Recognition , 2020, pp. 4085–4095
2020
Closest in time.
I. Oikonomidis, N. Kyriazis, and A. Argyros, “Full Dof Tracking of a Hand Interacting with an Object by Modeling Occlusions and Physical Constraints,” in International Conference on Computer Vision , 2011, pp. 2088–2095
2095
Closest in time.