Writing study: Efficiently Reconstructing Dynamic Scenes One D4RT at a Time

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← CVPR 2026 oral writing corpus

Chuhan Zhang, Guillaume Le Moing, Skanda Koppula, Ignacio Rocco, Liliane Momeni, Junyu Xie, Shuyang Sun, Rahul Sukthankar, Joëlle K. Barral, Raia Hadsell, Zoubin Ghahramani, Andrew Zisserman, Junlin Zhang, Mehdi S. M. Sajjadi · 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

11 physical pages

Before references / appendix

≈ 8.26 page-equivalents

Main figures / tables

6 / 9

Attached appendix figures / tables

0 / 0

Attached appendix span

Separate file recorded below; not in this PDF total

Before references / appendix: ≈ 75.09%References / intervening material: ≈ 24.91%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	≈ 0.97 pp.	8.82%
2. Method	2	≈ 2.4 pp.	21.82%
3. Related Work	4	≈ 0.74 pp.	6.73%
4. Experiments	5	≈ 3.42 pp.	31.09%
5. Conclusion	8	≈ 0.42 pp.	3.82%
References	9	≈ 2.74 pp.	24.91%

All detected figure and table locations

Main text

• Figure 1 · p. 1
• Figure 2 · p. 2
• Table 1 · p. 3
• Table 2 · p. 4
• Figure 3 · p. 4
• Figure 4 · p. 5
• Table 3 · p. 5
• Figure 5 · p. 6
• Table 4 · p. 6
• Table 5 · p. 7
• Table 6 · p. 7
• Figure 6 · p. 8
• Table 7 · p. 8
• Table 8 · p. 8
• Table 9 · 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 6 physical pages; 7 detected figures and 3 tables. These may include overlapping main-text material.

Located appendix only: starts on physical p.1; ≈ 5.88 page-equivalents, 7 figure labels and 3 table labels. This interval is distinct from the whole file.

Detected heading	PDF page	Estimated span
Appendix	1	≈ 0.05 pp.
A. Model Overview & Training Details	1	≈ 0.92 pp.
B. Generalization to Long Videos	2	≈ 1 pp.
C. High-Resolution Decoding with Subpixel Precision	3	≈ 1 pp.
D. Further Ablations	4	≈ 0.72 pp.
E. Further Qualitative Results	4	≈ 2.19 pp.

• Figure 7 · p. 1
• Figure 8 · p. 2
• Table 10 · p. 3
• Figure 9 · p. 3
• Table 11 · p. 4
• Figure 10 · p. 4
• Table 12 · p. 4
• Figure 11 · p. 5
• Figure 12 · p. 6
• Figure 13 · p. 6

Argument and organization

1. Problem and contribution

   Positions decoder redundancy and task-specific pipelines as the obstacle to efficient unified 4D understanding.

2. Argument sequence

   Defines the query interface first, derives several tasks from it, then explains architecture and training before broad evaluation.

3. Evidence and verification

   Table 1 is a task-to-query specification rather than a leaderboard; later plots/tables report pose-speed and track throughput at explicit FPS targets.

Problem, claim and contribution

Positions decoder redundancy and task-specific pipelines as the obstacle to efficient unified 4D understanding.

Introduction, pp. 1–2 · Main paper · Additional source 2

Argument and section order

Defines the query interface first, derives several tasks from it, then explains architecture and training before broad evaluation.

Section 2, pp. 2–4 · Main paper · Additional source 2

Figures, captions and visual explanation

Figure 2 color-codes spatial coordinates, source time, target time and camera frame through the query and output, preventing different time indices from collapsing visually.

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

Tables, comparisons and evidence

Table 1 is a task-to-query specification rather than a leaderboard; later plots/tables report pose-speed and track throughput at explicit FPS targets.

Table 1 and Algorithm 1, p. 3; Figure 3 and Table 3, pp. 4–5 · Main paper · Additional source 2

Appendix and reproducibility

Long-video stitching, high-resolution query/patch comparisons and public-only training results expand the evidence beyond a single standard resolution.

Supplement Appendices B–D, pp. 2–4 · Main paper · Additional source 2

Clarity and writing conventions

The caption and surrounding prose explicitly state that encoding is cached while queries are decoded independently.

Figure 2 and Section 2.1, p. 2 · Main paper · Additional source 2

What to reuse—and what not to infer

Transferable lesson: A unified model benefits from an interface table: show exactly which inputs vary to recover each advertised task.

Boundary: Throughput depends on query density, video length and hardware; a pose FPS number is not full dense-4D reconstruction FPS.

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 Sections 1–5, PDF pp. 1–8; references pp. 9–11: abstract/framing, section sequence, figure/table captions, evaluation organization and conclusions; not an exhaustive technical verification.

Appendix / supplement

Writing-oriented supplement scan: Supplement Appendices A–E, pp. 1–6: full architecture/training, long-video chunking, subpixel decoding, initialization/data ablations and examples. Video/code assets were not executed or assessed.

Visually inspected PDF pages

2, 3

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 · 11 pages
• Official CVF supplementary PDF · 6 pages