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:
| Lane |
What the lane cares about |
Adjacent venues to check |
| Rendering / light transport |
Noise, bias, convergence, speed, physical accuracy |
EGSR, HPG, TOG |
| Geometry processing |
Robustness on real meshes, guarantees, generality |
SGP, TOG |
| Animation / character |
Naturalness, control, temporal coherence |
SCA, TOG |
| Physical simulation |
Stability, energy behavior, time-step, scale |
SCA, TOG |
| Imaging / computational photography |
Reconstruction quality, artifacts, hardware |
ICCP, TOG |
| Geometry/appearance capture, fabrication |
Fidelity to real objects, manufacturability |
TOG, EG |
| Learning for graphics (neural rendering, generative 3D) |
Quality, generality, controllability |
CVPR/ICCV overlap, TOG |
| Interaction / VR-AR-MR, HCI-for-graphics |
Latency, presence, usability |
CHI/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>
Source: brycewang-stanford/Awesome-Journal-Skills → SIGGRAPH-Skills/skills/siggraph-related-work/SKILL.md
1---2name: siggraph-related-work3description: 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.4---567# SIGGRAPH Related Work89At SIGGRAPH, related work is where you convince a domain-expert reviewer that your contribution is10**new capability**, not a rediscovery. Graphics reviewers know the canon and the current11state-of-the-art in your sub-area intimately; a missed or mischaracterized prior method is a fast12reject. Position by **capability delta** — what prior methods cannot do that yours can — not by13chronology. Anchor venue facts to `resources/official-source-map.md`.1415## Know the lanes1617SIGGRAPH's scope spans distinct sub-communities, each with its own canon and its own reviewers.18Place your paper in the right lane(s) and cover that lane's recent state-of-the-art:1920| Lane | What the lane cares about | Adjacent venues to check |21|---|---|---|22| Rendering / light transport | Noise, bias, convergence, speed, physical accuracy | EGSR, HPG, TOG |23| Geometry processing | Robustness on real meshes, guarantees, generality | SGP, TOG |24| Animation / character | Naturalness, control, temporal coherence | SCA, TOG |25| Physical simulation | Stability, energy behavior, time-step, scale | SCA, TOG |26| Imaging / computational photography | Reconstruction quality, artifacts, hardware | ICCP, TOG |27| Geometry/appearance capture, fabrication | Fidelity to real objects, manufacturability | TOG, EG |28| Learning for graphics (neural rendering, generative 3D) | Quality, generality, controllability | CVPR/ICCV overlap, TOG |29| Interaction / VR-AR-MR, HCI-for-graphics | Latency, presence, usability | CHI/UIST overlap, TOG |3031A paper often sits in two lanes (e.g., neural rendering = rendering + learning). Cover both; a32reviewer from either lane will check that their canon is represented.3334## Capability-delta positioning3536For each closest prior method, state the axis on which you differ and by how much:3738- **Quality:** "Prior method X leaves visible noise below N samples; ours converges at N/4."39- **Speed:** "X runs offline; ours is real-time at the same quality."40- **Generality:** "X assumes manifold input; ours handles the non-manifold meshes practitioners41 actually have."42- **Robustness:** "X diverges on stiff configurations; ours remains stable."4344Never leave the comparison at "we are related to X." Name the axis, and back it with a comparison45in the Results (see `siggraph-experiments`). The strongest baseline must appear both here and in a46head-to-head figure/table.4748## Attribution discipline (venue collisions are common)4950Graphics ideas migrate across venues; attribute precisely:5152- **SIGGRAPH vs SIGGRAPH Asia vs TOG-direct.** All three publish in ACM TOG. Cite the specific53 issue; do not say "SIGGRAPH" for a SIGGRAPH Asia or a rolling TOG paper.54- **SIGGRAPH vs Eurographics (EG/CGF).** Many canonical techniques debuted at Eurographics or in55 Computer Graphics Forum, not SIGGRAPH — check dblp before attributing a method to SIGGRAPH.56- **Specialized venues.** EGSR (rendering), SGP (geometry), SCA (animation/simulation), HPG57 (high-performance graphics), I3D (interactive 3D), ICCP (computational photography) host founding58 papers routinely misattributed to SIGGRAPH.59- **The vision overlap.** Neural rendering / generative-3D work has a large CVPR/ICCV literature;60 cite it, and be clear which contribution is the graphics advance versus the vision one.6162## Self-positioning and blinding6364SIGGRAPH review has historically been **single-blind** (authors visible), so citing your own prior65work in the natural voice is usually fine — **but confirm the current cycle's policy** (**待核实**66for 2026). If a cycle requires anonymized review, cite your prior work in the third person and67avoid "our previous system X."6869## Anti-patterns7071- A chronological literature tour with no capability delta.72- Omitting the single strongest baseline because it is inconvenient — the reviewer knows it exists.73- Attributing an Eurographics/EGSR/SCA method to SIGGRAPH (or vice versa) without checking dblp.74- Treating a CVPR neural-rendering line as if it did not exist because "this is a graphics venue."75- Positioning against a strawman instead of the current state-of-the-art in the lane.7677## Output format7879```text80[Lanes] which sub-community/-ies; is each lane's SOTA covered? yes/no81[Strongest baseline] named here and compared head-to-head in Results? yes/no82[Deltas] <prior method -> axis (quality/speed/generality/robustness) -> magnitude>83[Attribution] SIGGRAPH vs SA vs TOG vs EG/EGSR/SGP/SCA checked on dblp? yes/no84[Blinding] cycle policy confirmed; self-cite voice correct? yes/no85[Fixes] <ordered>86```8788---8990**Source:** [`brycewang-stanford/Awesome-Journal-Skills`](https://github.com/brycewang-stanford/Awesome-Journal-Skills) → `SIGGRAPH-Skills/skills/siggraph-related-work/SKILL.md`