3D Shape Recognition

Description from the archive archive 2025-07-28.

Benchmarks archive 2025-07-28

No benchmark for this task in the archive.

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

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Parent tasks archive 2025-07-28

Most implemented papers archive 2025-07-28

15 shown of 15 papers with code (35 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.

• Set Transformer: A Framework for Attention-based Permutation-Invariant Neural Networks
  1 Oct 2018 9 repositories listed Syntology ran 5 of 9 samples · 4 unverified · 4 pointer-only (licence)
  Many machine learning tasks such as multiple instance learning, 3D shape recognition, and few-shot image classification are defined on sets of instances.
• MVTN: Multi-View Transformation Network for 3D Shape Recognition
  26 Nov 2020 2 repositories listed Syntology ran 3 of 3 samples · 0 unverified · 3 pointer-only (licence)
  MVTN exhibits clear performance gains in the tasks of 3D shape classification and 3D shape retrieval without the need for extra training supervision.
• On Learning Sets of Symmetric Elements
  20 Feb 2020 2 repositories listed Syntology ran 0 of 1 samples · 1 unverified
  We first characterize the space of linear layers that are equivariant both to element reordering and to the inherent symmetries of elements, like translation in the case of images.
• Learning Discriminative 3D Shape Representations by View Discerning Networks
  11 Aug 2018 2 repositories listed
  In this network, a Score Generation Unit is devised to evaluate the quality of each projected image with score vectors.
• Shape and Texture Recognition in Large Vision-Language Models
  29 Mar 2025 1 repository listed
  The ability to identify shapes regardless of orientation, texture, or context, and to recognize textures independently of their associated objects, is essential for general visual understanding of the world.
• Group Multi-View Transformer for 3D Shape Analysis with Spatial Encoding
  27 Dec 2023 1 repository listed
  The large model GMViT achieves excellent 3D classification and retrieval results on the benchmark datasets ModelNet, ShapeNetCore55, and MCB.
• MVTN: Learning Multi-View Transformations for 3D Understanding
  27 Dec 2022 1 repository listed
  Multi-view projection techniques have shown themselves to be highly effective in achieving top-performing results in the recognition of 3D shapes.
• PointMCD: Boosting Deep Point Cloud Encoders via Multi-view Cross-modal Distillation for 3D Shape Recognition
  7 Jul 2022 1 repository listed
  In this paper, we explore the possibility of boosting deep 3D point cloud encoders by transferring visual knowledge extracted from deep 2D image encoders under a standard teacher-student distillation workflow.
• Points to Patches: Enabling the Use of Self-Attention for 3D Shape Recognition
  8 Apr 2022 1 repository listed
  While the Transformer architecture has become ubiquitous in the machine learning field, its adaptation to 3D shape recognition is non-trivial.
• NeuralTailor: Reconstructing Sewing Pattern Structures from 3D Point Clouds of Garments
  31 Jan 2022 1 repository listed Syntology ran 0 of 3 samples · 3 unverified
  The fields of SocialVR, performance capture, and virtual try-on are often faced with a need to faithfully reproduce real garments in the virtual world.
• PolyNet: Polynomial Neural Network for 3D Shape Recognition with PolyShape Representation
  15 Oct 2021 1 repository listed
  3D shape representation and its processing have substantial effects on 3D shape recognition.
• Learning Canonical View Representation for 3D Shape Recognition with Arbitrary Views
  16 Aug 2021 1 repository listed Syntology ran 2 of 3 samples · 1 unverified · 3 pointer-only (licence)
  In this way, each 3D shape with arbitrary views is represented by a fixed number of canonical view features, which are further aggregated to generate a rich and robust 3D shape representation for shape recognition.
• View-GCN: View-Based Graph Convolutional Network for 3D Shape Analysis
  1 Jun 2020 1 repository listed
  View-based approach that recognizes 3D shape through its projected 2D images has achieved state-of-the-art results for 3D shape recognition.
• PVNet: A Joint Convolutional Network of Point Cloud and Multi-View for 3D Shape Recognition
  23 Aug 2018 1 repository listed
  With the recent proliferation of deep learning, various deep models with different representations have achieved the state-of-the-art performance.
• Beam Search for Learning a Deep Convolutional Neural Network of 3D Shapes
  14 Dec 2016 1 repository listed
  Each state of the beam search corresponds to a candidate CNN.

Syntology lines on 5 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.