eccv-reproducibility
Use when hardening the reproducibility story of an ECCV paper — training recipes and schedules readers can re-run, dataset versioning and split provenance, pinned foundation-model dependencies, compute disclosure, and seed/variance honesty for benchmark deltas, sized for the 14-page LNCS body plus supplement.
Profile →npx skills add brycewang-stanford/Awesome-Journal-Skills --skill eccv-reproducibility --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# ECCV Reproducibility Use this before the ECCV paper freeze. ECCV publishes through Springer LNCS with no standing mandatory reproducibility checklist across cycles (whether the current cycle adds one: 待核实 against the live author guidelines), so the reproducibility bar is enforced socially: by reviewers who try to match your numbers, and by the two-year gap before you could publish a correction at the same venue. ## The two-year checkability horizon A CVPR paper's errors are challenged within a year; an ECCV paper sits as the venue's latest word on the topic until the *next even year*. Write the paper so a lab starting from only the PDF plus supplement in 2027 can rebuild the result — that is the horizon reviewers implicitly price in. ## Recipe ledger (goes in paper or supplement, never nowhere) | Ingredient | Minimum disclosure | Common ECCV-draft omission | |---|---|---| | Training schedule | Optimizer, LR schedule, epochs/iterations, batch size, augmentations | Augmentation list "standard" with no definition | | Initialization | Pretrained checkpoint identity + source | "ImageNet-pretrained" without which checkpoint | | Data | Dataset version, split definition, filtering rules
- The two-year checkability horizon
- Recipe ledger (goes in paper or supplement, never nowhere)
- Foundation-model era pinning
- Variance honesty on benchmark deltas
- Split the story across the 14 pages and the supplement
- Honest-failure statement
- Output format
What does the eccv-reproducibility skill do?
Use when hardening the reproducibility story of an ECCV paper — training recipes and schedules readers can re-run, dataset versioning and split provenance, pinned foundation-model dependencies, compute disclosure, and seed/variance honesty for benchmark deltas, sized for the 14-page LNCS body plus supplement.
How do I install it?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill eccv-reproducibility --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From brycewang-stanford/Awesome-Journal-Skills, a repository with 909 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.