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The Segmentation Anything Model (SAM) requires labor-intensive data labeling.
Normalized cuts and image segmentation
J. Shi and J. Malik · 2000
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Conditional random fields: Probabilistic models for segmenting and labeling sequence data
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Divide and conquer: How object files adapt when a persisting object splits into two
S. R. Mitroff, B. J. Scholl, and K. Wynn · 2004
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Imagenet: A large-scale hierarchical image database
J. Deng, W. Dong, R. Socher, L.-J. Li, K. Li, and L. Fei-Fei · 2009
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Contour detection and hierarchical image segmentation
P. Arbelaez, M. Maire, C. Fowlkes, and J. Malik · 2010
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Microsoft coco: Common objects in context
T.-Y. Lin, M. Maire, S. Belongie, J. Hays, P. Perona, D. Ramanan, P. Dollár, and C. L. Zitnick · 2014
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Unsupervised object discovery and localization in the wild: Part-based matching with bottom-up region proposals, 2015
M. Cho, S. Kwak, C. Schmid, and J. Ponce · 2015
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Deep residual learning for image recognition
K. He, X. Zhang, S. Ren, and J. Sun · 2016
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Lvis: A dataset for large vocabulary instance segmentation
A. Gupta, P. Dollar, and R. Girshick · 2019
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Unsupervised image matching and object discovery as optimization, 2019
H. V. Vo, F. Bach, M. Cho, K. Han, Y. LeCun, P. Perez, and J. Ponce · 2019
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Semantic understanding of scenes through the ade20k dataset
B. Zhou, H. Zhao, X. Puig, T. Xiao, S. Fidler, A. Barriuso, and A. Torralba · 2019
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Hierarchical structure is employed by humans during visual motion perception
J. Bill, H. Pailian, S. J. Gershman, and J. Drugowitsch · 2020
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Language models are few-shot learners
T. Brown, B. Mann, N. Ryder, M. Subbiah, J. D. Kaplan, P. Dhariwal, A. Neelakantan, P. Shyam, G. Sastry, A. Askell, et al · 2020
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Cascadepsp: Toward class-agnostic and very high-resolution segmentation via global and local refinement
H. K. Cheng, J. Chung, Y.-W. Tai, and C.-K. Tang · 2020
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An image is worth 16x16 words: Transformers for image recognition at scale
A. Dosovitskiy, L. Beyer, A. Kolesnikov, D. Weissenborn, X. Zhai, T. Unterthiner, M. Dehghani, M. Minderer, G. Heigold, S. Gelly, et al · 2020
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Scaling laws for neural language models
J. Kaplan, S. McCandlish, T. Henighan, T. B. Brown, B. Chess, R. Child, S. Gray, A. Radford, J. Wu, and D. Amodei · 2020
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Toward unsupervised, multi-object discovery in large-scale image collections
H. V. Vo, P. Pérez, and J. Ponce · 2020
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Solov2: Dynamic and fast instance segmentation
X. Wang, R. Zhang, T. Kong, L. Li, and C. Shen · 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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Swin transformer: Hierarchical vision transformer using shifted windows
Z. Liu, Y. Lin, Y. Cao, H. Hu, Y. Wei, Z. Zhang, S. Lin, and B. Guo · 2021
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Localizing objects with self-supervised transformers and no labels
O. Siméoni, G. Puy, H. V. Vo, S. Roburin, S. Gidaris, A. Bursuc, P. Pérez, R. Marlet, and J. Ponce · 2021
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A. Q. Jiang, A. Sablayrolles, A. Mensch, C. Bamford, D. S. Chaplot, D. d. l. Casas, F. Bressand, G. Lengyel, G. Lample, L. Saulnier, et al · 2023
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A. Kirillov, E. Mintun, N. Ravi, H. Mao, C. Rolland, L. Gustafson, T. Xiao, S. Whitehead, A. C. Berg, W.-Y. Lo, P. Dollár, and R. Girshick · 2023
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Semantic-sam: Segment and recognize anything at any granularity
F. Li, H. Zhang, P. Sun, X. Zou, S. Liu, J. Yang, C. Li, L. Zhang, and J. Gao · 2023
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Paco: Parts and attributes of common objects
V. Ramanathan, A. Kalia, V. Petrovic, Y. Wen, B. Zheng, B. Guo, R. Wang, A. Marquez, R. Kovvuri, A. Kadian, et al · 2023
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B. Cheng, I. Misra, A. G. Schwing, A. Kirillov, and R. Girdhar · 2022
Cited alongside, same era.
Partimagenet: A large, high-quality dataset of parts
J. He, S. Yang, S. Yang, A. Kortylewski, X. Yuan, J.-N. Chen, S. Liu, C. Yang, Q. Yu, and A. Yuille · 2022
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Masked autoencoders are scalable vision learners
K. He, X. Chen, S. Xie, Y. Li, P. Dollár, and R. Girshick · 2022
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Image segmentation using text and image prompts
T. Lüddecke and A. Ecker · 2022
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Open world entity segmentation
L. Qi, J. Kuen, Y. Wang, J. Gu, H. Zhao, P. Torr, Z. Lin, and J. Jia · 2022
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Discovering object masks with transformers for unsupervised semantic segmentation
W. Van Gansbeke, S. Vandenhende, and L. Van Gool · 2022
Cited alongside, same era.
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
Cited alongside, same era.
G. Team, R. Anil, S. Borgeaud, Y. Wu, J.-B. Alayrac, J. Yu, R. Soricut, J. Schalkwyk, A. M. Dai, A. Hauth, et al · 2023
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Llama: Open and efficient foundation language models
H. Touvron, T. Lavril, G. Izacard, X. Martinet, M.-A. Lachaux, T. Lacroix, B. Rozière, N. Goyal, E. Hambro, F. Azhar, et al · 2023
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Attention is all you need, 2023
A. Vaswani, N. Shazeer, N. Parmar, J. Uszkoreit, L. Jones, A. N. Gomez, L. Kaiser, and I. Polosukhin · 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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Seggpt: Segmenting everything in context
X. Wang, X. Zhang, Y. Cao, W. Wang, C. Shen, and T. Huang · 2023
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Tokencut: Segmenting objects in images and videos with self-supervised transformer and normalized cut
Y. Wang, X. Shen, Y. Yuan, Y. Du, M. Li, S. X. Hu, J. L. Crowley, and D. Vaufreydaz · 2023
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Efficientsam: Leveraged masked image pretraining for efficient segment anything, 2023
Y. Xiong, B. Varadarajan, L. Wu, X. Xiang, F. Xiao, C. Zhu, X. Dai, D. Wang, F. Sun, F. Iandola, R. Krishnamoorthi, and V. Chandra · 2023
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Fast segment anything, 2023
X. Zhao, W. Ding, Y. An, Y. Du, T. Yu, M. Li, M. Tang, and J. Wang · 2023
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SOHES: Self-supervised open-world hierarchical entity segmentation
S. Cao, J. Gu, J. Kuen, H. Tan, R. Zhang, H. Zhao, A. Nenkova, L. Gui, T. Sun, and Y.-X. Wang · 2024
Closest in time.
Unsupervised universal image segmentation
D. Niu, X. Wang, X. Han, L. Lian, R. Herzig, and T. Darrell · 2024
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Videocutler: Surprisingly simple unsupervised video instance segmentation
X. Wang, I. Misra, Z. Zeng, R. Girdhar, and T. Darrell · 2024
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Yi: Open foundation models by 01. ai
A. Young, B. Chen, C. Li, C. Huang, G. Zhang, G. Zhang, H. Li, J. Zhu, J. Chen, J. Chang, et al · 2024
Closest in time.