What is recorded here?
Introduced a homogeneous multi-branch residual block and cardinality as a model-design axis, with an equivalent grouped-convolution implementation for the selected bottleneck structure.
Source-linked catalogue note. A detailed explanatory guide has not yet been prepared for this entry.
Scientific scope
Grouped convolution, residual learning and split-transform-merge precedents are inherited. The displayed equivalence depends on the chosen homogeneous blocks and need not hold for arbitrary heterogeneous transformations. Matched-complexity accuracy advantages are empirical, not a theorem that cardinality always beats width/depth.
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People and systems
Saining Xie; Ross Girshick; Piotr Dollár; Zhuowen Tu; Kaiming He
Source-listed authors or explicitly credited technical contributors for the cited versions. Family entries retain source-specific attribution; a combined list is not one original-paper byline or equal individual work. Names alone do not establish resolved identities.
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English catalogue narrative
ResNeXt: aggregated residual transformations
Introduced a homogeneous multi-branch residual block and cardinality as a model-design axis, with an equivalent grouped-convolution implementation for the selected bottleneck structure.
Scientific scope
Grouped convolution, residual learning and split-transform-merge precedents are inherited. The displayed equivalence depends on the chosen homogeneous blocks and need not hold for arbitrary heterogeneous transformations. Matched-complexity accuracy advantages are empirical, not a theorem that cardinality always beats width/depth.
Reading status
This is a source-linked WRS catalogue note. A full explanatory guide and independent scientific reconstruction have not been completed for this entry. Read the identified original work for its complete narrative and arguments.
People and systems
Saining Xie; Ross Girshick; Piotr Dollár; Zhuowen Tu; Kaiming He
Source-listed authors or explicitly credited technical contributors for the cited versions. Family entries retain source-specific attribution; a combined list is not one original-paper byline or equal individual work. Names alone do not establish resolved identities.