wacv-artifact-evaluation
Use when packaging code, data, and models for a WACV paper, covering the anonymous review artifact versus the public post-acceptance release, reproducing constraint-based applications claims (latency, power, robustness) not just accuracy, dataset licensing and release, and keeping the artifact in sync across the two-round Revise-and-Resubmit lap.
Profile →npx skills add brycewang-stanford/Awesome-Journal-Skills --skill wacv-artifact-evaluation --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.
# WACV Artifact Evaluation Use this to build the two artifacts a WACV paper needs: a **sealed anonymous package** for review and a **public release** after acceptance. WACV's applications framing means the artifact must let a reviewer reproduce a *deployed* claim, and the two-round model means the artifact must survive a revision. Facts are the WACV 2026/2027 cycles as read on 2026-07-09. ## Two artifacts, two audiences | | Anonymous review artifact | Public post-acceptance release | |---|---|---| | Audience | Double-blind reviewers | The community, via CVF open access + IEEE Xplore paper | | Identity | Fully anonymized: no author names, repos, or org strings | De-anonymized; real repo, license, and citation | | Contents | Enough to reproduce the headline claims | Full code, weights, and dataset (or access instructions) | | Timing | With the submission / supplement | By the camera-ready obligation (see `wacv-camera-ready`) | Do not ship the review artifact with a link to a named GitHub repo or a project page — that breaks double-blind. Ship the code and a runnable path inside the anonymized package. ## Reproduce the claim, not just the metric For an Applications-track paper the hea
- Two artifacts, two audiences
- Reproduce the claim, not just the metric
- Datasets and licensing
- Sync across the two rounds
- Reverify each cycle
- Output format
What does the wacv-artifact-evaluation skill do?
Use when packaging code, data, and models for a WACV paper, covering the anonymous review artifact versus the public post-acceptance release, reproducing constraint-based applications claims (latency, power, robustness) not just accuracy, dataset licensing and release, and keeping the artifact in sync across the two-round Revise-and-Resubmit lap.
How do I install it?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill wacv-artifact-evaluation --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.