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Siggraph related work

Skill brycewang-stanford/Awesome-Journal-Skills/SIGGRAPH-Skills/skills/siggraph-related-work

Use when writing or auditing the related-work positioning of a SIGGRAPH / TOG paper, covering the computer-graphics literature lanes (rendering, geometry, animation, simulation, imaging, fabrication, learning-for-graphics), capability-delta positioning against the strongest prior method, and correct attribution across SIGGRAPH, SIGGRAPH Asia, TOG, EG/CGF, and sibling venues.From its SKILL.md

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SKILL.md

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SIGGRAPH Related Work

At SIGGRAPH, related work is where you convince a domain-expert reviewer that your contribution is new capability, not a rediscovery. Graphics reviewers know the canon and the current state-of-the-art in your sub-area intimately; a missed or mischaracterized prior method is a fast reject. Position by capability delta — what prior methods cannot do that yours can — not by chronology. Anchor venue facts to resources/official-source-map.md.

Know the lanes

SIGGRAPH's scope spans distinct sub-communities, each with its own canon and its own reviewers. Place your paper in the right lane(s) and cover that lane's recent state-of-the-art:

LaneWhat the lane cares aboutAdjacent venues to check
Rendering / light transportNoise, bias, convergence, speed, physical accuracyEGSR, HPG, TOG
Geometry processingRobustness on real meshes, guarantees, generalitySGP, TOG
Animation / characterNaturalness, control, temporal coherenceSCA, TOG
Physical simulationStability, energy behavior, time-step, scaleSCA, TOG
Imaging / computational photographyReconstruction quality, artifacts, hardwareICCP, TOG
Geometry/appearance capture, fabricationFidelity to real objects, manufacturabilityTOG, EG
Learning for graphics (neural rendering, generative 3D)Quality, generality, controllabilityCVPR/ICCV overlap, TOG
Interaction / VR-AR-MR, HCI-for-graphicsLatency, presence, usabilityCHI/UIST overlap, TOG

A paper often sits in two lanes (e.g., neural rendering = rendering + learning). Cover both; a reviewer from either lane will check that their canon is represented.

Capability-delta positioning

For each closest prior method, state the axis on which you differ and by how much:

  • Quality: "Prior method X leaves visible noise below N samples; ours converges at N/4."
  • Speed: "X runs offline; ours is real-time at the same quality."
  • Generality: "X assumes manifold input; ours handles the non-manifold meshes practitioners actually have."
  • Robustness: "X diverges on stiff configurations; ours remains stable."

Never leave the comparison at "we are related to X." Name the axis, and back it with a comparison in the Results (see siggraph-experiments). The strongest baseline must appear both here and in a head-to-head figure/table.

Attribution discipline (venue collisions are common)

Graphics ideas migrate across venues; attribute precisely:

  • SIGGRAPH vs SIGGRAPH Asia vs TOG-direct. All three publish in ACM TOG. Cite the specific issue; do not say "SIGGRAPH" for a SIGGRAPH Asia or a rolling TOG paper.
  • SIGGRAPH vs Eurographics (EG/CGF). Many canonical techniques debuted at Eurographics or in Computer Graphics Forum, not SIGGRAPH — check dblp before attributing a method to SIGGRAPH.
  • Specialized venues. EGSR (rendering), SGP (geometry), SCA (animation/simulation), HPG (high-performance graphics), I3D (interactive 3D), ICCP (computational photography) host founding papers routinely misattributed to SIGGRAPH.
  • The vision overlap. Neural rendering / generative-3D work has a large CVPR/ICCV literature; cite it, and be clear which contribution is the graphics advance versus the vision one.

Self-positioning and blinding

SIGGRAPH review has historically been single-blind (authors visible), so citing your own prior work in the natural voice is usually fine — but confirm the current cycle's policy (待核实 for 2026). If a cycle requires anonymized review, cite your prior work in the third person and avoid "our previous system X."

Anti-patterns

  • A chronological literature tour with no capability delta.
  • Omitting the single strongest baseline because it is inconvenient — the reviewer knows it exists.
  • Attributing an Eurographics/EGSR/SCA method to SIGGRAPH (or vice versa) without checking dblp.
  • Treating a CVPR neural-rendering line as if it did not exist because "this is a graphics venue."
  • Positioning against a strawman instead of the current state-of-the-art in the lane.

Output format

[Lanes] which sub-community/-ies; is each lane's SOTA covered? yes/no
[Strongest baseline] named here and compared head-to-head in Results? yes/no
[Deltas] <prior method -> axis (quality/speed/generality/robustness) -> magnitude>
[Attribution] SIGGRAPH vs SA vs TOG vs EG/EGSR/SGP/SCA checked on dblp? yes/no
[Blinding] cycle policy confirmed; self-cite voice correct? yes/no
[Fixes] <ordered>

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