Writing study: PPISP: Physically-Plausible Compensation and Control of Photometric Variations in Radiance Field Reconstruction

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← CVPR 2026 oral writing corpus

Isaac Deutsch, Nicolas Moënne-Loccoz, Gavriel State, Žan Gojčič · 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: Domain-grounded methods & physical systems (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

10 physical pages

Before references / appendix

≈ 8.05 page-equivalents

Main figures / tables

4 / 5

Attached appendix figures / tables

0 / 0

Attached appendix span

Separate file recorded below; not in this PDF total

Before references / appendix: ≈ 80.5%References / intervening material: ≈ 19.5%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	1	≈ 0.59 pp.	5.9%
2. Related Work	2	≈ 0.95 pp.	9.5%
3. Preliminaries	3	≈ 0.54 pp.	5.4%
4. Method	3	≈ 2.32 pp.	23.2%
5. Experiments	6	≈ 2.51 pp.	25.1%
6. Conclusion and Limitations	8	≈ 0.23 pp.	2.3%
7. Acknowledgments	8	≈ 0.13 pp.	1.3%
References	9	≈ 1.95 pp.	19.5%

All detected figure and table locations

Main text

• Figure 1 · p. 1
• Figure 2 · p. 3
• Figure 3 · p. 5
• Figure 4 · p. 6
• Table 1 · p. 7
• Table 2 · p. 7
• Table 3 · p. 7
• Table 4 · p. 8
• Table 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 4 tables. These may include overlapping main-text material.

Located appendix only: starts on physical p.1; ≈ 6.93 page-equivalents, 6 figure labels and 4 table labels. This interval is distinct from the whole file.

Detected heading	PDF page	Estimated span
Supplementary Material	1	≈ 0.14 pp.
A. Additional Experiments	1	≈ 1.57 pp.
B. Additional Method Details	2	≈ 2.89 pp.
C. Additional Experiment Details	5	≈ 1.42 pp.
D. Manual Control	7	≈ 0.91 pp.

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

Argument and organization

1. Problem and contribution

   PPISP argues that appearance compensation should support novel views without access to their target pixels. This separates a practical inference requirement from merely fitting training-image brightness and color.

2. Argument sequence

   Radiance and camera-formation preliminaries introduce the variables before exposure, vignetting, color correction, response function and controller modules. Evaluation then separates novel-view quality, metadata, runtime and train-versus-test capacity.

3. Evidence and verification

   Table 1 groups results by dataset and reconstruction backbone and explicitly labels controller present versus omitted. Table 2 removes individual physical components, while Table 3 records whether metadata is supplied, so different information regimes are not silently mixed.

Problem, claim and contribution

PPISP argues that appearance compensation should support novel views without access to their target pixels. This separates a practical inference requirement from merely fitting training-image brightness and color.

Introduction; problem discussion before Section 3, PDF p.3 · Main paper · Additional source 2

Argument and section order

Radiance and camera-formation preliminaries introduce the variables before exposure, vignetting, color correction, response function and controller modules. Evaluation then separates novel-view quality, metadata, runtime and train-versus-test capacity.

Sections 3–5 · Main paper · Additional source 2

Figures, captions and visual explanation

Figure 2 shows the same photometric pipeline in two training phases and uses frozen/trainable symbols to identify what changes. A row of intermediate images underneath turns exposure, vignetting and color correction into visible operations.

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

Tables, comparisons and evidence

Table 1 groups results by dataset and reconstruction backbone and explicitly labels controller present versus omitted. Table 2 removes individual physical components, while Table 3 records whether metadata is supplied, so different information regimes are not silently mixed.

Tables 1–3, PDF p.7 · Main paper · Additional source 2

Appendix and reproducibility

The supplement discusses online calibration and parameter ambiguity, supplies implementation and experiment settings, and demonstrates manual controls. Those details qualify physical interpretability rather than suggesting every inferred parameter is uniquely identifiable.

Supplementary Sections A–D, PDF pp.1–7 · Main paper · Additional source 2

Clarity and writing conventions

The paper distinguishes raw PSNR from color-corrected PSNR and reports novel-view rather than only training-view benefits. Its runtime table identifies incremental compensation overhead relative to a rendering baseline.

Table 1; Section 5 and Tables 4–5, PDF pp.7–8 · Main paper · Additional source 2

What to reuse—and what not to infer

Transferable lesson: For correction modules, draw training phases explicitly, show intermediate transformed images, and keep target-pixel access and metadata availability visible in comparisons.

Boundary: Physically plausible modules do not imply uniquely recovered camera settings or support for every unmodeled camera effect; preserve the identifiability and inference-input qualifications.

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

Writing-oriented scan throughout main PDF pp.1–8 and references pp.9–10: abstract/framing, section sequence, figure/table captions, evaluation organization and conclusions; not an exhaustive technical verification.

Appendix / supplement

Writing-oriented supplement scan: all seven supplementary PDF pages covering calibration ambiguities, implementation, settings and manual controls. Video/code assets were not executed or assessed.

Visually inspected PDF pages

3, 7

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 CVF open-access CVPR 2026 accepted-paper PDF · 10 pages
• Official CVF supplementary ZIP member PDF; see URL fragment for member · 7 pages