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Simulated Gaussian Manipulation
5 papers with code · 0 benchmarks · 0 datasets archive 2025-07-28
Simulated Gaussian Manipulation is the development of high-level robotic manipulation of 3D objects generated by Gaussian splatting
Description from the archive archive 2025-07-28.
Benchmarks archive 2025-07-28
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Datasets archive 2025-07-28
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Parent tasks archive 2025-07-28
Most implemented papers archive 2025-07-28
5 shown of 5 papers with code (6 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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12 Mar 2025 1 repository listedTo address this, we propose Motion Blender Gaussian Splatting (MBGS), a novel framework that uses motion graphs as an explicit and sparse motion representation.
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26 Sep 2024 1 repository listed Syntology ran 1 of 1 samples · 0 unverified · 1 pointer-only (licence)This analysis-by-synthesis approach uses part-centric feature fields in an iterative optimization which enables the use of geometric regularizers to recover 3D motions from only a single video.
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7 May 2024 1 repository listed Syntology ran 3 of 3 samples · 0 unverified · 1 pointer-only (licence)ASK-Splat enables geometric, semantic, and affordance understanding of 3D scenes, which is critical in many robotics tasks; (ii) SEE-Splat, a real-time scene-editing module using 3D semantic masking and infilling to…
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14 Mar 2024 1 repository listed Syntology ran 8 of 8 samples · 0 unverified · 8 pointer-only (licence)In particular, we propose an Efficient Feature Distillation (EFD) module that employs contrastive learning to efficiently and accurately distill language embeddings derived from foundational models.
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13 Mar 2024 1 repository listed Syntology ran 4 of 6 samples · 2 unverifiedPerforming language-conditioned robotic manipulation tasks in unstructured environments is highly demanded for general intelligent robots.
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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