Writing study: OccuFly: A 3D Vision Benchmark for Semantic Scene Completion from the Aerial Perspective

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← CVPR 2026 oral writing corpus

Markus Gross, Sai B. Matha, Aya Fahmy, Rui Song, Daniel Cremers, Henri Meeß · Official CVPR 2026 oral record

Observed writing choices, not acceptance rules. This study examines the inspected manuscript version. It does not establish why the paper was accepted or that its presentation choices should be copied unchanged.

Figure, table and section ledger

Editorial contribution type: Datasets, benchmarks & measurement (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

12 physical pages

Before references / appendix

≈ 8.05 page-equivalents

Main figures / tables

5 / 5

Attached appendix figures / tables

0 / 0

Attached appendix span

Separate file recorded below; not in this PDF total

Before references / appendix: ≈ 67.08%References / intervening material: ≈ 32.92%Estimated layout envelopes, not text/artwork area. Unresolved appendix boundaries remain within the undivided post-body material.

Extraction notes: No attached appendix boundary detected. Zero means no recognized caption, not independently verified absence.

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	≈ 0.68 pp.	5.67%
2. Related Work	2	≈ 1.03 pp.	8.58%
3. Data Generation Framework	3	≈ 2.39 pp.	19.92%
4. OccuFly Dataset	6	≈ 1.23 pp.	10.25%
5. Benchmark Experiments	7	≈ 1.44 pp.	12%
6. Conclusion	8	≈ 0.22 pp.	1.83%
References	9	≈ 3.95 pp.	32.92%

All detected figure and table locations

Main text

• Figure 1 · p. 1
• Figure 2 · p. 3
• Table 1 · p. 6
• Table 2 · p. 6
• Table 3 · p. 6
• Figure 3 · p. 7
• Table 4 · p. 7
• Table 5 · p. 7
• Figure 4 · p. 8
• Figure 5 · p. 8

Attached appendix

No recognized caption labels.

Separate source files—excluded from canonical-PDF totals

A separate author version may repeat main text and references. Whole-file lengths and counts are not extra appendix material and are never added to the canonical PDF totals. Read the study's source scope for which sections received substantive reading versus layout inspection.

Additional source 1

Separate PDF (or ZIP containing it): whole-file layout of 7 physical pages; 6 detected figures and 7 tables. These may include overlapping main-text material.

Located appendix only: starts on physical p.1; ≈ 6.93 page-equivalents, 6 figure labels and 7 table labels. This interval is distinct from the whole file.

Detected heading	PDF page	Estimated span
Supplementary Material	1	≈ 0.02 pp.
7. Scene-Level Visualizations	1	≈ 0.07 pp.
8. Implementation Details	1	≈ 0.74 pp.
9. Additional OccuFly Dataset Evaluation	1	≈ 2.42 pp.
10. Additional Benchmark Evaluation	4	≈ 3.68 pp.

• Table 6 · p. 1
• Table 7 · p. 1
• Figure 6 · p. 2
• Table 8 · p. 3
• Table 9 · p. 3
• Figure 7 · p. 3
• Table 10 · p. 4
• Figure 8 · p. 4
• Figure 9 · p. 4
• Table 11 · p. 5
• Figure 10 · p. 5
• Table 12 · p. 6
• Figure 11 · p. 7

Argument and organization

1. Data generation §3

   Define the voxel-label problem and detail reconstruction, label lifting, densification and sampling.

2. Dataset and benchmark §§4–5

   Audit acquisition/statistics and ground truth before testing scene completion and depth transfer.

Problem, claim and contribution

The introduction identifies a terrestrial-to-aerial domain gap and a sensing/annotation bottleneck, so the dataset and generation pipeline jointly answer the motivation.

Abstract and introduction, PDF pp. 1–2 · Main paper · Additional source 2

Argument and section order

The paper devotes a method section to ground-truth creation before reporting dataset scale, preventing the number of samples from substituting for an explanation of label quality.

§§3–4, PDF pp. 3–6 · Main paper · Additional source 2

Figures, captions and visual explanation

Figure 2 divides the data pipeline into numbered stages and distinguishes surface, occluded and invalid masks; this makes the meaning of an occupancy label visible.

Figure 2, PDF p. 3 · Main paper · Additional source 2

Tables, comparisons and evidence

Table 1 lists scene identity, season, environment, area and altitude counts by split. The benchmark later separates occupancy/semantics and zero-shot/fine-tuned depth so failure of one capability is not hidden by another.

Table 1, PDF p. 6; Tables 4–5, PDF p. 7 · Main paper · Additional source 2

Appendix and reproducibility

The supplement expands annotation ratios, class frequencies, scene reprojection errors, acquisition overlap and altitude/class-wise results, linking label construction to evaluation difficulty.

Supplement §§7–10, PDF pp. 1–7; Tables 7–12 and Figure 11 · Main paper · Additional source 2

Clarity and writing conventions

The qualitative depth discussion specifies a single metric colormap across methods, and the conclusion retains static-scene and cross-altitude temporal-consistency limitations.

§5.3 and conclusion, PDF p. 8 · Main paper · Additional source 2

What to reuse—and what not to infer

Transferable lesson: A dataset paper should document how labels are produced and which regions are valid, then expose splits and domain factors before presenting baseline scores.

Boundary: Many image samples from nine scenes are not the same as many independent environments; photogrammetric consistency is not an independent full audit of all semantic labels or dynamic objects.

Apply this lesson using the argument and evidence worksheet.

Inspection record and sources

Checked

2026-09-26

Reading status

Writing-focused manuscript scan + selected visuals inspected

Main text

Manuscript-wide writing scan of PDF pp. 1–12: framing, argument sequence, section organization, figure/table captions, evaluation interpretation and limitations; reference sections identified. This is a writing-focused scan, not an exhaustive technical proof or reproduction audit. Main PDF pages 3 and 6 were rendered and visually inspected.

Appendix / supplement

Writing-focused scan of the separate supplementary PDF, pp. 1–7, including its organization, captions, protocol/evidence detail and limitation material where present; proofs and code listings were inspected for exposition, not independently verified or executed. Supplement §§7–10, PDF pp. 1–7; Tables 7–12 and Figure 11. Linked video/audio demonstrations and non-PDF archive contents were not assessed.

Visually inspected PDF pages

3, 6

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.

• Official CVPR 2026 CVF open-access accepted manuscript; retrieved 2026-09-26 · 12 pages
• Official CVPR 2026 CVF supplementary PDF; retrieved 2026-09-26 · 7 pages