Writing study: MAGICIAN: Efficient Long-Term Planning with Imagined Gaussians for Active Mapping
← CVPR 2026 oral writing corpus
Shiyao Li, Antoine Guédon, Shizhe Chen, Vincent Lepetit · Official CVPR 2026 oral record
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
- ≈ 8.12 page-equivalents
- Main figures / tables
- 8 / 5
- Attached appendix figures / tables
- 0 / 0
- Attached appendix span
- Separate file recorded below; not in this PDF total
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.
All detected figure and table locations
Main text
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 8 physical pages; 3 detected figures and 4 tables. These may include overlapping main-text material.
Located appendix only: starts on physical p.1; ≈ 7.93 page-equivalents, 3 figure labels and 4 table labels. This interval is distinct from the whole file.
Argument and organization
- Method §§3.1–3.5
Define the exploration objective, derive coverage gain, introduce occupancy/Gaussians and then the planner.
- Experiments §§4.1–4.3
State embodiment configurations, compare mapping quality and analyze search horizon/replanning choices.
Problem, claim and contribution
The opening distinguishes active mapping with known poses from passive SLAM, then ties greedy viewpoints to inefficient reconstruction coverage.
§1, PDF p. 2 · Main paper · Additional source 2
Argument and section order
The coverage-gain objective precedes the representation and planner, making fast rendering a means of enabling long-horizon search rather than an unrelated graphics component.
§§3.2–3.5, PDF pp. 3–5 · Main paper · Additional source 2
Figures, captions and visual explanation
Figure 2 closes the loop from RGB-D observations to occupancy, novelty fields, candidate trajectories and execution. The caption distinguishes planning depth from the shorter action prefix actually executed.
Figure 2, PDF p. 3 · Main paper · Additional source 2
Tables, comparisons and evidence
Table 1 exposes different robot action spaces, camera height, resolution and step budgets; reconstruction quality is evaluated from a fixed 100-image trajectory sample with a common reconstruction method.
Table 1 and Figure 5, PDF p. 6; Figure 6, PDF p. 7 · Main paper · Additional source 2
Appendix and reproducibility
The supplement adds per-scene coverage/AUC, variance across starting poses, sampling-density sensitivity and failure analysis of poor early occupancy prediction.
Supplement §§A–C, PDF pp. 1–8; Tables 6–9 and Figure 9 · Main paper · Additional source 2
Clarity and writing conventions
Beam width, look-ahead depth and replanning frequency have separate analyses, so long-term planning quality is not confused with an unspecified larger compute budget.
Figures 7–8, PDF p. 8 · Main paper · Additional source 2
What to reuse—and what not to infer
Transferable lesson: For a planning system, show the closed loop and execution horizon explicitly, then report both exploration efficiency and reconstruction quality under disclosed embodiment budgets.
Boundary: Strong results with known poses and a learned occupancy prior are not demonstrated robustness to arbitrary real robotic localization errors; early incomplete geometry remains a reported failure mode.
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
- Writing-focused scan of the separate supplementary PDF, pp. 1–8, 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 §§A–C, PDF pp. 1–8; Tables 6–9 and Figure 9. 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.