Writing study: Streaming Diffusion Model for Fast Infrared and Visible Video Fusion

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← CVPR 2026 oral writing corpus

Jinyuan Liu, Ludan Sun, Tengyu Ma, Chunyan Yang, Zhiying Jiang, Long Ma, Risheng Liu, Xin Fan · 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: Efficiency, inference & 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

9 / 3

Attached appendix figures / tables

0 / 0

Attached appendix span

No boundary detected; not assumed zero

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	≈ 1.27 pp.	12.7%
2. Related work	2	≈ 0.7 pp.	7%
3. Motivation	3	≈ 0.39 pp.	3.9%
4. Methodology	3	≈ 2.57 pp.	25.7%
5. Experiment	6	≈ 2.48 pp.	24.8%
6. Conclusion	8	≈ 0.1 pp.	1%
Acknowledgments	8	≈ 0.15 pp.	1.5%
References	9	≈ 1.95 pp.	19.5%

All detected figure and table locations

Main text

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

Attached appendix

No recognized caption labels.

Argument and organization

1. Temporal failure and two-stage training

   Motivate video-specific artifacts before introducing image-level pretraining and streaming adaptation.

2. Fusion quality to downstream utility

   Evaluate fusion metrics, temporal differences, component distributions, tracking and efficiency separately.

Problem, claim and contribution

The main tension is explicit: independent-frame fusion flickers, but iterative video diffusion is too slow for streaming use.

Introduction and Section 3, PDF pp. 1–3 · Main paper

Argument and section order

A dedicated motivation section bridges related work and the two-stage method, with the loss defined after the temporal mechanism rather than before its role is known.

Sections 3–4, PDF pp. 3–5 · Main paper

Figures, captions and visual explanation

The architecture labels Stage I and Stage II and expands the memory adapter below. On page 6, frame-difference maps and per-frame metric curves provide complementary visualizations of temporal behavior.

Figure 2, PDF p. 3; Figures 4–5, PDF p. 6; visual inspection · Main paper

Tables, comparisons and evidence

Tracking is evaluated separately from fusion quality, and efficiency analysis admits a larger parameter count while arguing for lower runtime/FLOPs.

Sections 5.5–5.6, Table 3 and Figure 9, PDF pp. 7–8 · Main paper

Appendix and reproducibility

No separate supplemental PDF is listed in the official inventory. The main manuscript carries qualitative ablations, violin plots, tracking and efficiency material, so the main evaluation section supplies the available writing evidence.

Figures 6–9 and Tables 2–3, PDF pp. 7–8; official proceedings record · Main paper

Clarity and writing conventions

Temporal consistency has its own subsection instead of being inferred from still-frame examples alone.

Section 5.3, PDF p. 6 · Main paper

What to reuse—and what not to infer

Transferable lesson: A video paper should visualize change through time, not only attractive frames; connect temporal diagnostics to a downstream task and a deployment budget.

Boundary: Frame-difference maps are diagnostics, not complete proof of temporal correctness; the aligned infrared/visible input assumption and tested hardware remain part of the scope.

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. 1–10: 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

No separate supplemental PDF is listed in the official inventory; the writing study uses the main manuscript. Linked project demonstrations and external code were not executed.

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 · 10 pages