Group Normalization
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Diffusion Policy: Visuomotor Policy Learning via Action Diffusion
Chi, C., Xu, Z., Feng, S., Cousineau, E., Du, Y., Burchfiel, B., Tedrake, R., & Song, S. (2023) · arXiv · doi:10.48550/arxiv.2303.04137 · Cited by 12 · see citing works
“(2) Replace BatchNorm with GroupNorm (Wu and He, 2018) for stable training.”
Person identity shift for privacy-preserving person re-identification
Dou, S., Jiang, X., Zhao, Q., Wang, Y., Li, D., & Zhao, C. (2026) · Science China Information Sciences · doi:10.1007/s11432-023-4583-x · Cited by 2 · see citing works
Baz, M. (2024) · Mathematics · doi:10.3390/math12213320 · Cited by 1 · see citing works
- Authors
- Wu, Y., & He, K.
- Affiliations
- Meta (United States) (US)
- Corresponding author
- He, Kaiming
- ORCID
- Venue
- International Journal of Computer Vision
- Published
- 2019-07-22
- Volume
- 128
- Issue
- 3
- Pages
- 742-755
- ISSN
- 0302-9743 (ISSN-L)
- 0920-5691
- 1573-1405
- OpenAlex
- W2795783309
- Cited by
- 3,601
- References
- 0
- Citations by year
- 2026: 399 · 2025: 578 · 2024: 599 · 2023: 445 · 2022: 497 · 2021: 502 · 2020: 388 · 2019: 183 · 2018: 10
- FWCI
- 81.61
- Type
- conference paper
- Language
- en
- Open access
- green
- arxiv.org
- Locations
- Lecture notes in computer science (publishedVersion)
- International Journal of Computer Vision (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- arXiv (Cornell University)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Neural Network Applications
- Physical Sciences › Computer Science › Artificial Intelligence › Domain Adaptation and Few-Shot Learning
- Physical Sciences › Computer Science › Artificial Intelligence › Stochastic Gradient Optimization Techniques
- Keywords
- group normalization, batch normalization, small batch sizes, pre-training and fine-tuning, object detection, semantic segmentation, video classification, ResNet50
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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