Writing study: SparseWorld-TC: Trajectory-Conditioned Sparse Occupancy World Model

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← CVPR 2026 oral writing corpus

Jiayuan Du, Yiming Zhao, Zhenglong Guo, Yong Pan, Wenbo Hou, Zhihui Hao, Kun Zhan, Qijun Chen · 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: 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

10 physical pages

Before references / appendix

≈ 8.05 page-equivalents

Main figures / tables

6 / 4

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	≈ 0.96 pp.	9.6%
2. Related Work	2	≈ 0.88 pp.	8.8%
3. Methodology	3	≈ 3.2 pp.	32%
4. Experiments	6	≈ 2.43 pp.	24.3%
5. Conclusion	8	≈ 0.1 pp.	1%
Acknowledgments	8	≈ 0.12 pp.	1.2%
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. 4
• Figure 4 · p. 5
• Table 1 · p. 6
• Table 2 · p. 7
• Table 3 · p. 7
• Table 4 · p. 7
• Figure 5 · p. 8
• Figure 6 · 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 5 physical pages; 7 detected figures and 7 tables. These may include overlapping main-text material.

Located appendix only: starts on physical p.1; ≈ 4.94 page-equivalents, 7 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.
A. Additional Quantitative Experiments	1	≈ 0.97 pp.
B. Additional Qualitative Experiments	2	≈ 3.95 pp.

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

Argument and organization

1. Problem and contribution

   SparseWorld-TC motivates future occupancy prediction conditioned on a planned ego trajectory, not unconditional scene completion. It contrasts its sparse representation with intermediate dense BEV/voxel pipelines.

2. Argument sequence

   Representation and trajectory definitions precede the spatial–temporal fusion architecture and losses. Experiments then separate short-horizon comparisons, longer forecasts and trajectory-conditioning effects.

3. Evidence and verification

   Table 1 separates occupancy-ground-truth inputs from camera inputs and explicitly excludes the ego trajectory from that input-column shorthand. It reports semantic and geometric metrics by horizon alongside FPS; longer-horizon and trajectory ablations are separate tables.

Problem, claim and contribution

SparseWorld-TC motivates future occupancy prediction conditioned on a planned ego trajectory, not unconditional scene completion. It contrasts its sparse representation with intermediate dense BEV/voxel pipelines.

Introduction; Section 3.1 · Main paper · Additional source 2

Argument and section order

Representation and trajectory definitions precede the spatial–temporal fusion architecture and losses. Experiments then separate short-horizon comparisons, longer forecasts and trajectory-conditioning effects.

Sections 3.1–3.3; Section 4 · Main paper · Additional source 2

Figures, captions and visual explanation

Figure 2 explains how an anchor predicts point offsets and semantic logits before the full model diagram introduces temporal attention. Later forecast panels align times and trajectories so the meaning of alternative futures can be inspected.

Figures 2–4, PDF pp.3–5; Figure 6 · Main paper · Additional source 2

Tables, comparisons and evidence

Table 1 separates occupancy-ground-truth inputs from camera inputs and explicitly excludes the ego trajectory from that input-column shorthand. It reports semantic and geometric metrics by horizon alongside FPS; longer-horizon and trajectory ablations are separate tables.

Table 1, PDF p.6; Tables 2–3, PDF p.7 · Main paper · Additional source 2

Appendix and reproducibility

The supplement adds RayIoU, embedding ablations, memory use, class-specific behavior and convergence/failures. These checks extend the efficiency and prediction claims beyond a single average occupancy score.

Supplementary PDF pp.1–5 · Main paper · Additional source 2

Clarity and writing conventions

The paper distinguishes absent, predicted and ground-truth trajectory conditions in its analysis. That precise input labeling is more transferable than a broad statement that the model predicts the future.

Trajectory ablation, Table 3; Section 4 · Main paper · Additional source 2

What to reuse—and what not to infer

Transferable lesson: For forecasting, make horizon, conditioning information and input modality part of the result layout, not assumptions hidden in experimental prose.

Boundary: A qualitative long rollout does not establish equal quantitative accuracy at that horizon; ground-truth trajectory or occupancy access is not interchangeable with deployable predicted input.

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 five supplementary PDF pages, including alternative metrics, embeddings, memory, class-level results, convergence and failure cases. Video/code assets were not executed or 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 CVF open-access CVPR 2026 accepted-paper PDF · 10 pages
• Official CVF supplementary PDF · 5 pages