Writing study: Text-to-3D by Stitching a Multi-view Reconstruction Network to a Video Generator

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← ICLR 2026 oral writing corpus

Hyojun Go, Dominik Narnhofer, Goutam Bhat, Prune Truong, Federico Tombari, Konrad Schindler · Official ICLR 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 design (primary) · Learning & optimization algorithms.

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

31 physical pages

Before references / appendix

≈ 10.11 page-equivalents

Main figures / tables

6 / 5

Attached appendix figures / tables

10 / 2

Attached appendix span

≈ 12.89 page-equivalents

Before references / appendix: ≈ 32.61%References / intervening material: ≈ 25.81%Attached appendix: ≈ 41.58%Estimated layout envelopes, not text/artwork area. Unresolved appendix boundaries remain within the undivided post-body material.

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	2	≈ 1.26 pp.	4.06%
2 RELATED WORKS	3	≈ 1.27 pp.	4.1%
3 METHODOLOGY	4	≈ 1.78 pp.	5.74%
4 EXPERIMENTAL RESULTS	6	≈ 4.21 pp.	13.58%
5 CONCLUSION	10	≈ 0.21 pp.	0.68%
6 ACKNOWLEDGMENTS	10	≈ 0.28 pp.	0.9%
REFERENCES	11	≈ 8 pp.	25.81%
A EXTENDED RELATED WORKS	19	≈ 0.52 pp.	1.68%
B METHODOLOGY DETAILS AND IMPLEMENTATION	19	≈ 1.89 pp.	6.1%
C DETAILS ON EXPERIMENTAL SETUPS	21	≈ 1.91 pp.	6.16%
D FURTHER ABLATION STUDIES	23	≈ 2.35 pp.	7.58%
E ADDITIONAL RESULTS	25	≈ 1.95 pp.	6.29%
F LIMITATIONS	27	≈ 0.14 pp.	0.45%
G USE OF LARGE LANGUAGE MODELS	27	≈ 4.13 pp.	13.32%

All detected figure and table locations

Main text

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

Attached appendix

• Table 6 · p. 23
• Figure 7 · p. 24
• Figure 8 · p. 25
• Figure 9 · p. 26
• Table 7 · p. 26
• Figure 10 · p. 27
• Figure 11 · p. 28
• Figure 12 · p. 29
• Figure 13 · p. 29
• Figure 14 · p. 30
• Figure 15 · p. 31
• Figure 16 · p. 31

Argument and organization

1. Decoder reuse and latent alignment as two bottlenecks

   Derive the two-component contribution from limitations of prior pipelines

2. Stitching followed by reward finetuning

   Specify which pretrained components are preserved and adapted

3. Generation and reconstruction evaluation

   Test both new synthesis capability and retained geometric competence

Problem, claim and contribution

The introduction identifies separately a weak newly trained 3D decoder and a mismatch between generated latents and decoder inputs. This yields a clean motivation for stitching plus alignment, rather than presenting a disconnected list of techniques.

Section 1, pages 2–3 · Main paper

Argument and section order

The method first fits a linear bridge to a selected 3D-network layer, then finetunes against original-network outputs and aligns the video generator. The footnote candidly distinguishes its conventional 3D-VAE name from a literal variational autoencoder.

Sections 3.1–3.2; page 4 footnote 1 · Main paper

Figures, captions and visual explanation

Figure 3 separates stitching and reward stages with colored boundaries, frozen/trainable symbols and explicit gradient paths. Figure 7 pairs decoded frames with reconstructed renderings, making dynamic-content ghosting and alignment failures visually interpretable.

Page 4, Figure 3; page 24, Figure 7 · Main paper

Tables, comparisons and evidence

The evaluation separates text-to-3D synthesis from image-conditioned reconstruction. Crucially, Appendix C.2 discloses 100 per-scene refinement steps for MVDUSt3R splats; this variant should not be described as wholly optimization-free at inference.

Sections 4.2–4.3; Appendix C.2, page 22 · Main paper

Appendix and reproducibility

Equal-wall-clock reward ablations reveal that consistency-only tuning can hurt imaging quality: 38.67 versus 54.56 for multi-view-only. The full model recovers 64.87, while quality-only remains better on aesthetic and CLIP metrics.

Appendix D.1, Table 6, page 23 · Main paper

Clarity and writing conventions

Appendix E appropriately limits MSE selection to comparisons within a fixed model pairing; absolute MSE does not rank different VAEs. Appendix F adds an essential operational limitation: images must form a coherent sequence, not an arbitrary unordered set.

Pages 26–27, Figure 10 and Appendix F · Main paper

What to reuse—and what not to infer

Transferable lesson: For foundation-model composition, show module boundaries and trainability, evaluate retained abilities separately, and disclose every test-time refinement hidden behind a feedforward headline.

Boundary: No new 3D labels does not mean no pretrained supervision or training data. Differentiable reward finetuning is not PPO, selected-step backpropagation is not full untruncated differentiation, and generated pointmaps are evaluated qualitatively only.

Apply this lesson using the argument and evidence worksheet.

Inspection record and sources

Checked

2026-09-19

Reading status

Full text + selected visuals inspected

Main text

Pages 1–10, Sections 1–6; references 11–18

Appendix / supplement

Pages 19–31, Appendices A–G, implementation, complete evaluation protocols, ablations, qualitative captions, limitations and AI disclosure

Visually inspected PDF pages

4, 24

• official ICLR 2026 proceedings PDF · 31 pages