siggraph-experiments
Use when designing or auditing the evaluation of a SIGGRAPH / TOG paper, covering head-to-head comparisons against the strongest prior method, ablations, performance/timing reporting with hardware, image/geometry quality metrics, perceptual and user studies, and matching the evidence to the graphics claim shape.
Profile →npx skills add brycewang-stanford/Awesome-Journal-Skills --skill siggraph-experiments --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.
# SIGGRAPH Experiments SIGGRAPH acceptance turns on **evidence proportional to a graphics claim**: a technique that claims to be faster must be timed against a real baseline on stated hardware; one that claims higher quality must be compared, quantitatively and visually, against the strongest prior method. This skill matches evaluation to claim shape and pre-empts the domain-expert reviewer's first objections. Anchor policy to `resources/official-source-map.md`. ## Match evidence to the claim | Claim shape | Evidence the reviewer expects | Common failure | |---|---|---| | "Higher quality" | Head-to-head vs SOTA with a metric (PSNR/SSIM/LPIPS/FLIP; Hausdorff/normal error for geometry) + side-by-side visuals + video | Only one's own results shown; no baseline | | "Faster / real-time" | Wall-clock vs baseline at **equal quality**, with GPU/CPU, driver, resolution | Timing at unequal quality; no hardware stated | | "More general / robust" | Results across a broad, non-cherry-picked scene set incl. hard cases | Works only on the paper's three easy inputs | | "New capability" | Demonstrations prior methods provably cannot produce | Capability asserted, not shown against a method that fai
- Match evidence to the claim
- The comparison is the evaluation
- Metrics, honestly
- Performance and timing are first-class
- Perceptual and user studies
- Ablations isolate the contribution
- Anti-patterns
- Output format
What does the siggraph-experiments skill do?
Use when designing or auditing the evaluation of a SIGGRAPH / TOG paper, covering head-to-head comparisons against the strongest prior method, ablations, performance/timing reporting with hardware, image/geometry quality metrics, perceptual and user studies, and matching the evidence to the graphics claim shape.
How do I install it?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill siggraph-experiments --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.