Transparent Object Depth Estimation

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.

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

3 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

4 shown of 4 papers with code (4 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.

• TODE-Trans: Transparent Object Depth Estimation with Transformer
  18 Sep 2022 1 repository listed
  We observe that the global characteristics of the transformer make it easier to extract contextual information to perform depth estimation of transparent areas.
• TransCG: A Large-Scale Real-World Dataset for Transparent Object Depth Completion and a Grasping Baseline
  17 Feb 2022 1 repository listed
  However, the majority of current grasping algorithms would fail in this case since they heavily rely on the depth image, while ordinary depth sensors usually fail to produce accurate depth information for transparent…
• SuperCaustics: Real-time, open-source simulation of transparent objects for deep learning applications
  23 Jul 2021 1 repository listed
  In particular, these synthetic datasets omit features such as refraction, dispersion and caustics due to limitations in the rendering pipeline.
• ClearGrasp: 3D Shape Estimation of Transparent Objects for Manipulation
  6 Oct 2019 1 repository listed Syntology ran 0 of 8 samples · 8 unverified
  To address these challenges, we present ClearGrasp -- a deep learning approach for estimating accurate 3D geometry of transparent objects from a single RGB-D image for robotic manipulation.

Syntology lines on 1 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.