Use this while drafting or compressing an ECCV manuscript. The defining constraint is the format: LNCS single-column, 14 pages including figures and tables, references-only pages after that. This is a different craft from the two-column CVF page — more words per page, cheaper full-width figures, costlier white space — and the template changed after 2024, so write in the current kit from day one.
| Budget line | Typical allocation | LNCS-specific note |
|---|---|---|
| Title, abstract, intro | 2.0 pages | Single column makes long intros tempting; cap at 1.25 pages of prose |
| Related work | 1.0 page | Numbered [n] citations pack tightly; group by idea, not by paper |
| Method | 3.5–4.5 pages | Full-width architecture figures are cheap here — use one, not three |
| Experiments | 4.5–5.5 pages | Tables span the full text width; design them wide and few |
| Limitations + conclusion | 0.5–1.0 page | An honest limitations paragraph is expected |
| Figures/tables total | counted inside the 14 | The submission limit includes them — every figure displaces prose |
The inclusion of figures in the limit is the discipline lever: each figure must either carry an argument (teaser, method overview, failure modes) or compress one (results curves). Decorative variants go to the supplement.
An ECCV first page must work for the adjacent-niche reviewer (see
eccv-review-process): by the end of page 1 a non-specialist should be able
to say what input becomes what output, why current methods fail at it, and
what single idea fixes it.
\subsubsection depth is where LNCS headings stop looking like headings;
restructure rather than nest.Every headline sentence should be defensible in two rebuttal lines later:
Fragile: "Our method significantly outperforms all prior work."
Sized: "On <benchmark vX>, our method improves <metric> by <d> over
<strongest baseline> under matched <backbone/training data>."
Fragile: "generalizes to arbitrary scenes"
Sized: "generalizes across the N categories of <dataset>; unseen
domains are evaluated in Sec. 5.4 and remain open"
Scope every superlative to benchmark + protocol + substrate. In a foundation-model era, unmatched pretraining data is the first rebuttal attack surface — declare the substrate in the claim itself.
[Style verdict] submit-ready / restructure / compress / re-scope claims
[Page ledger] <section -> pages vs budget, figure share>
[First-page test] <what an adjacent-niche reader retains, or fails to>
[Fragile claims] <sentence -> sized rewrite>
[Pass order] <which of the five passes remain>