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.
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.
For each closest prior method, state the axis on which you differ and by how much:
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.
Graphics ideas migrate across venues; attribute precisely:
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."
[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>