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Learning object-centric representations from complex natural environments enables both humans and machines with reasoning abilities from low-level perceptual features.
The pascal visual object classes (voc) challenge
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Delving deeper into the whorl of flower segmentation
M. Nilsback and A. Zisserman · 2010
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Caltech-ucsd birds 200
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Novel dataset for fine-grained image categorization
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Scikit-learn: Machine learning in Python
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Microsoft COCO: common objects in context
T. Lin, M. Maire, S. J. Belongie, L. D. Bourdev, R. B. Girshick, J. Hays, P. Perona, D. Ramanan, P. Dollár, and C. L. Zitnick · 2014
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Coco-stuff: Thing and stuff classes in context
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Fixing weight decay regularization in adam
I. Loshchilov and F. Hutter · 2017
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J. T. Rolfe · 2017
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A. Vaswani, N. Shazeer, N. Parmar, J. Uszkoreit, L. Jones, A. N. Gomez, L. Kaiser, and I. Polosukhin · 2017
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Deepusps: Deep robust unsupervised saliency prediction with self-supervision
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Basnet: Boundary-aware salient object detection
X. Qin, Z. Zhang, C. Huang, C. Gao, M. Dehghan, and M. Jägersand · 2019
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End-to-end object detection with transformers
N. Carion, F. Massa, G. Synnaeve, N. Usunier, A. Kirillov, and S. Zagoruyko · 2020
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Space-time correspondence as a contrastive random walk
A. Jabri, A. Owens, and A. A. Efros · 2020
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Object-centric learning with slot attention
F. Locatello, D. Weissenborn, T. Unterthiner, A. Mahendran, G. Heigold, J. Uszkoreit, A. Dosovitskiy, and T. Kipf · 2020
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Object-centric diagnosis of visual reasoning
J. Yang, J. Mao, J. Wu, D. Parikh, D. D. Cox, J. B. Tenenbaum, and C. Gan · 2020
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Emerging properties in self-supervised vision transformers
M. Caron, H. Touvron, I. Misra, H. Jégou, J. Mairal, P. Bojanowski, and A. Joulin · 2021
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An empirical study of training self-supervised vision transformers
X. Chen, S. Xie, and K. He · 2021
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Picie: Unsupervised semantic segmentation using invariance and equivariance in clustering
J. H. Cho, U. Mall, K. Bala, and B. Hariharan · 2021
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Infoseg: Unsupervised semantic image segmentation with mutual information maximization
R. Harb and P. Knöbelreiter · 2021
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Kubric: A scalable dataset generator
K. Greff, F. Belletti, L. Beyer, C. Doersch, Y. Du, D. Duckworth, D. J. Fleet, D. Gnanapragasam, F. Golemo, C. Herrmann, T. Kipf, A. Kundu, D. Lagun, I. H. Laradji, H. D. Liu, H. Meyer, Y. Miao, D. Nowrouzezahrai, A. C. Öztireli, E. Pot, N. Radwan, D. Rebain, S. Sabour, M. S. M. Sajjadi, M. Sela, V. Sitzmann, A. Stone, D. Sun, S. Vora, Z. Wang, T. Wu, K. M. Yi, F. Zhong, and A. Tagliasacchi · 2022
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Unsupervised semantic segmentation by distilling feature correspondences
M. Hamilton, Z. Zhang, B. Hariharan, N. Snavely, and W. T. Freeman · 2022
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Masked autoencoders are scalable vision learners
K. He, X. Chen, S. Xie, Y. Li, P. Dollár, and R. B. Girshick · 2022
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Acseg: Adaptive conceptualization for unsupervised semantic segmentation, 2022
K. Li, Z. Wang, Z. Cheng, R. Yu, Y. Zhao, G. Song, C. Liu, L. Yuan, and J. Chen · 2022
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https://bo-qsa.github.io/, 2022
Y. Liu · 2022
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T. Kipf, G. F. Elsayed, A. Mahendran, A. Stone, S. Sabour, G. Heigold, R. Jonschkowski, A. Dosovitskiy, and K. Greff · 2021
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Boundary-aware segmentation network for mobile and web applications
X. Qin, D. Fan, C. Huang, C. Diagne, Z. Zhang, A. C. Sant’Anna, A. Suàrez, M. Jägersand, and L. Shao · 2021
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Deepcut: Unsupervised segmentation using graph neural networks clustering
A. Aflalo, S. Bagon, T. Kashti, and Y. C. Eldar · 2022
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Object-centric compositional imagination for visual abstract reasoning
R. Assouel, P. Taslakian, D. Vazquez, P. Rodriguez, and Y. Bengio · 2022
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Masked siamese networks for label-efficient learning
M. Assran, M. Caron, I. Misra, P. Bojanowski, F. Bordes, P. Vincent, A. Joulin, M. Rabbat, and N. Ballas · 2022
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Discovering objects that can move
Z. Bao, P. Tokmakov, A. Jabri, Y. Wang, A. Gaidon, and M. Hebert · 2022
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Learning pixel trajectories with multiscale contrastive random walks
Z. Bian, A. Jabri, A. A. Efros, and A. Owens · 2022
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M. Seitzer, M. Horn, A. Zadaianchuk, D. Zietlow, T. Xiao, C. Simon-Gabriel, T. He, Z. Zhang, B. Schölkopf, T. Brox, and F. Locatello · 2022
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Illiterate DALL-E learns to compose
G. Singh, F. Deng, and S. Ahn · 2022
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Simple unsupervised object-centric learning for complex and naturalistic videos
G. Singh, Y. Wu, and S. Ahn · 2022
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Freesolo: Learning to segment objects without annotations
X. Wang, Z. Yu, S. De Mello, J. Kautz, A. Anandkumar, C. Shen, and J. M. Alvarez · 2022
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Self-supervised visual representation learning with semantic grouping
X. Wen, B. Zhao, A. Zheng, X. Zhang, and X. Qi · 2022
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Rethinking alignment and uniformity in unsupervised image semantic segmentation
D. Zhang, C. Li, H. Li, W. Huang, L. Huang, and J. Zhang · 2022
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Invariant slot attention: Object discovery with slot-centric reference frames
O. Biza, S. van Steenkiste, M. S. M. Sajjadi, G. F. Elsayed, A. Mahendran, and T. Kipf · 2023
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Improving object-centric learning with query optimization
B. Jia, Y. Liu, and S. Huang · 2023
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Cut and learn for unsupervised object detection and instance segmentation
X. Wang, R. Girdhar, S. X. Yu, and I. Misra · 2023
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Unsupervised semantic segmentation with self-supervised object-centric representations
A. Zadaianchuk, M. Kleindessner, Y. Zhu, F. Locatello, and T. Brox · 2023
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