Generative 3D Object Classification

Description from the archive archive 2025-07-28.

Benchmarks archive 2025-07-28

2 leaderboard tables shown for this task, 2 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.

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.

Parent tasks archive 2025-07-28

Most implemented papers archive 2025-07-28

5 shown of 5 papers with code (5 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.

• Point-Bind & Point-LLM: Aligning Point Cloud with Multi-modality for 3D Understanding, Generation, and Instruction Following
  1 Sep 2023 5 repositories listed Syntology ran 13 of 20 samples · 7 unverified · 7 pointer-only (licence)
  We introduce Point-Bind, a 3D multi-modality model aligning point clouds with 2D image, language, audio, and video.
• 3D-LLM: Injecting the 3D World into Large Language Models
  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.
• ShapeLLM: Universal 3D Object Understanding for Embodied Interaction
  27 Feb 2024 3 repositories listed Syntology ran 9 of 17 samples · 8 unverified
  This 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.
• PointLLM: Empowering Large Language Models to Understand Point Clouds
  31 Aug 2023 3 repositories listed
  The 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.
• MiniGPT-3D: Efficiently Aligning 3D Point Clouds with Large Language Models using 2D Priors
  2 May 2024 1 repository listed
  Notably, MiniGPT-3D gains an 8.

Syntology lines on 3 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.