Writing study: Consistent 3D Surface Flow Model with Global State
← NeurIPS 2026 oral writing corpus
Antoine Guedon, Shu Nakamura, Nicolas Dufour, Jiahui Lei, Ko Nishino, Angjoo Kanazawa · Official NeurIPS 2026 oral record
Figure, table and section ledger
Editorial contribution type: Architecture & representation (primary).
Layout extraction, not a required paper template. Counts are distinct caption labels; a multi-panel figure counts once. Section spans are estimated from heading positions, including floats and whitespace. Method and limitations.
- Canonical PDF
- 22 physical pages
- Before references / appendix
- ≈ 10.42 page-equivalents
- Main figures / tables
- 6 / 5
- Attached appendix figures / tables
- 1 / 0
- Attached appendix span
- ≈ 4.91 page-equivalents
Source-bound correction: Top-level heading and reference/appendix boundaries checked against source PDF text. Bibliography titles/author initials, numbered contribution/property bullets, diagram steps, equations and TOC entries are not substantive headings. Section spans are page-coordinate estimates, not ink area or prose-only length. This is an author manuscript mirror, not a verified accepted-version template. Source layout uses physical single-column y/page-height, including equation-heavy pages.
Section-by-section lengths and source pages
The title/abstract/front matter precede the first numbered heading. A span ends at the next detected top-level heading, not at the last sentence; end-page whitespace is included. References and statements are listed separately. These are not measurements of text-only or artwork area.
| Top-level heading | Starts on PDF page | Estimated span | Share of entire PDF |
|---|---|---|---|
| 1 Introduction | 2 | ≈ 1.32 pp. | 6% |
| 2 Method | 3 | ≈ 2.4 pp. | 10.91% |
| 3 Experiments | 5 | ≈ 3.92 pp. | 17.82% |
| 4 Related Work | 9 | ≈ 1.04 pp. | 4.73% |
| 5 Conclusion | 10 | ≈ 0.54 pp. | 2.45% |
| 6 Acknowledgments | 11 | ≈ 0.11 pp. | 0.5% |
| References | 11 | ≈ 6.67 pp. | 30.32% |
| A Related work | 18 | ≈ 1.38 pp. | 6.27% |
| B Architecture details | 19 | ≈ 1.11 pp. | 5.05% |
| C Training | 20 | ≈ 0.77 pp. | 3.5% |
| D Guidance | 21 | ≈ 0.47 pp. | 2.14% |
| E Evaluation protocol. | 21 | ≈ 1.17 pp. | 5.32% |
All detected figure and table locations
Main text
Attached appendix
Argument and organization
- Global state motivation
Connects viewpoint redundancy to a fixed-size scene representation.
- Encoder, decoder and guidance
Explains the three interventions in the same order as the central architecture figure.
- Quality, resolution and ablations
Tests shared-state reconstruction under controlled view counts and separates native from generated reference surfaces.
Problem, claim and contribution
The argument begins with geometry being independent of viewpoint, then derives why a shared latent should not grow with the number of views. This links the representation choice to the problem rather than introducing a module without a need.
Introduction; Section 2 · Main paper
Argument and section order
Encoder, flow decoder and guidance become explicit subsections matching the three-part method overview. The later study varies view count, output resolution and individual design choices.
Sections 2.1–2.3 and 3 · Main paper
Figures, captions and visual explanation
The diagram separates frozen VGGT features, latent compression, pointwise decoding and guidance. The resolution strip holds the latent fixed while increasing decoded points, making a design property visible rather than merely asserting flexibility.
Figure 2, PDF p. 3; Figure 5, p. 8 · Main paper
Tables, comparisons and evidence
Generated reference surfaces and native ground-truth surfaces have separate comparisons. Raw pointmaps are visually distinguished from globally fused surfaces, and the input-view budget is stated; these are essential conditions for interpreting ranks.
Tables 1–2; Table 2, PDF p. 8 · Main paper
Appendix and reproducibility
Related-work expansion, architecture settings, training surface preparation and guidance details are kept as named lookup routes. The main figure remains sufficient to locate the changed computation without reading every training setting.
Appendices A–D and evaluation details · Main paper
Clarity and writing conventions
Numbered ingredients and consistent encoder/decoder/guidance terminology create a short verbal map. Copy that consistency, not the assumption that the same three-part outline suits every architecture paper.
Figure 2 caption; Section 2 opening · Main paper
What to reuse—and what not to infer
Transferable lesson: Make an architectural invariant visible: identify what stays fixed, what scales, and which inference-time operations implement the intended property.
Boundary: The public title adds the name Surflo to the official program title; the author list matches. Its current arXiv rendering and results are not verified identical to the accepted copy.
Apply this lesson using the argument and evidence worksheet.
Inspection record and sources
- Checked
- 2026-10-02
- Reading status
- Writing-focused manuscript scan + selected visuals inspected
- Main text
- Writing-focused scan across framing, method organization, captions, result presentation and conclusion; title and author overlap checked against the official program. Selected physical pages inspected as rendered images.
- Appendix / supplement
- Attached appendix headings, reproduction routes and representative supporting prose/captions scanned. Long tables, every proof and every appendix page were not individually validated.
- Visually inspected PDF pages
- 3, 8
This is a writing-focused scan of the manuscript and the stated supplementary scope: framing, organization, visual explanation, evidence presentation and wording. It is not a line-by-line proof audit, reproduction of results or exhaustive scientific review.