Browse State-of-the-Art › 3D Object Captioning
3D Object Captioning
6 papers with code · 1 benchmark · 2 datasets archive 2025-07-28
3D object captioning involves generating a natural language description of an object, given its point cloud representation.
Description from the archive archive 2025-07-28.
Benchmarks archive 2025-07-28
1 leaderboard table shown for this task, 1 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted.
| Dataset | Best model (first row in archive order) | Paper | Code | Syntology | Compare |
|---|---|---|---|---|---|
| Objaverse (6 rows) | MiniGPT-3D | MiniGPT-3D: Efficiently Aligning 3D Point Clouds with Large... | code | — | Compare |
Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.
Libraries
Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.
Datasets archive 2025-07-28
2 datasets whose archive record lists this task, ordered by the archive's paper count.
Subtasks archive 2025-07-28
No subtask under this task in the archive's task tree.
Most implemented papers archive 2025-07-28
6 shown of 6 papers with code (7 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.
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24 Jul 2023 5 repositories listed Syntology ran 5 of 10 samples · 5 unverified · 10 pointer-only (licence)Furthermore, experiments on our held-in datasets for 3D captioning, task composition, and 3D-assisted dialogue show that our model outperforms 2D VLMs.
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27 Feb 2024 3 repositories listed Syntology ran 9 of 17 samples · 8 unverifiedThis paper presents ShapeLLM, the first 3D Multimodal Large Language Model (LLM) designed for embodied interaction, exploring a universal 3D object understanding with 3D point clouds and languages.
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31 Aug 2023 3 repositories listedThe unprecedented advancements in Large Language Models (LLMs) have shown a profound impact on natural language processing but are yet to fully embrace the realm of 3D understanding.
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26 Nov 2024 2 repositories listed Syntology ran 0 of 6 samples · 6 unverifiedGenerating high-fidelity 3D content from text prompts remains a significant challenge in computer vision due to the limited size, diversity, and annotation depth of the existing datasets.
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11 Apr 2024 2 repositories listed Syntology ran 3 of 3 samples · 0 unverified · 3 pointer-only (licence)Scalable annotation approaches are crucial for constructing extensive 3D-text datasets, facilitating a broader range of applications.
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2 May 2024 1 repository listedNotably, MiniGPT-3D gains an 8.
Syntology lines on 4 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.
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