mlsanityData to 7 Oct 2026

SHREC'22 Track: Sketch-Based 3D Shape Retrieval in the Wild

arXiv 2207.04945 ↗First posted 11 Jul 2022cs.CV cs.GR cs.MMcited by 9

Not on the map. Why?

Abstract (arXiv)

Sketch-based 3D shape retrieval (SBSR) is an important yet challenging task, which has drawn more and more attention in recent years. Existing approaches address the problem in a restricted setting, without appropriately simulating real application scenarios. To mimic the realistic setting, in this track, we adopt large-scale sketches drawn by amateurs of different levels of drawing skills, as well as a variety of 3D shapes including not only CAD models but also models scanned from real objects. We define two SBSR tasks and construct two benchmarks consisting of more than 46,000 CAD models, 1,700 realistic models, and 145,000 sketches in total. Four teams participated in this track and submitted 15 runs for the two tasks, evaluated by 7 commonly-adopted metrics. We hope that, the benchmarks, the comparative results, and the open-sourced evaluation code will foster future research in this direction among the 3D object retrieval community.

Key facts. Cited by 9 papers in the map (data through 7 Oct 2026). Builds on 16 of its 28 references that are in the map. First posted on arXiv 11 Jul 2022.

Builds on

16 of 28 references.

References · 16

  1. 2015Deep Residual Learning for Image Recognitioncited by 51,809
  2. 2014Very Deep Convolutional Networks for Large-Scale Image Recognitioncited by 15,267
  3. 2016PointNet: Deep Learning on Point Sets for 3D Classification and Segmentationcited by 5,223
  4. 2017Squeeze-and-Excitation Networkscited by 4,763
  5. 2015ShapeNet: An Information-Rich 3D Model Repositorycited by 2,880
  6. 2018Unsupervised Feature Learning via Non-Parametric Instance-level Discriminationcited by 1,838
  7. 2017Learning to Compare: Relation Network for Few-Shot Learningcited by 1,139
  8. 2021EfficientNetV2: Smaller Models and Faster Trainingcited by 1,127
  9. 2015Multi-view Convolutional Neural Networks for 3D Shape Recognitioncited by 564
  10. 2019Revisiting Point Cloud Classification: A New Benchmark Dataset and Classification Model on Real-World Datacited by 532
  11. 2022Rethinking Network Design and Local Geometry in Point Cloud: A Simple Residual MLP Frameworkcited by 376
  12. 2017A Neural Representation of Sketch Drawingscited by 311
4 more
  1. 2019Doodle to Search: Practical Zero-Shot Sketch-based Image Retrievalcited by 79
  2. 2017Deep Sketch Hashing: Fast Free-hand Sketch-Based Image Retrievalcited by 68
  3. 2018Deep Cross-modality Adaptation via Semantics Preserving Adversarial Learning for Sketch-based 3D Shape Retrievalcited by 7
  4. 2018Domain-Aware SE Network for Sketch-based Image Retrieval with Multiplicative Euclidean Margin Softmaxcited by 4

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 1; 2023: 3; 2024: 2; 2025: 1; 2026: 2.

9 papers.

  1. 2022Conjugate Product Graphs for Globally Optimal 2D-3D Shape Matchingcited by 6
  2. 2023TextANIMAR: Text-based 3D Animal Fine-Grained Retrievalcited by 4
  3. 2023VariGrad: A Novel Feature Vector Architecture for Geometric Deep Learning on Unregistered Datacited by 4
  4. 2023SketchANIMAR: Sketch-based 3D Animal Fine-Grained Retrievalcited by 3
  5. 2024Freeview Sketching: View-Aware Fine-Grained Sketch-Based Image Retrievalcited by 2
  6. 2024PReP: Efficient context-based shape retrieval for missing partscited by 0
  7. 2025SHREC 2025: Retrieval of Optimal Objects for Multi-modal Enhanced Language and Spatial Assistance (ROOMELSA)cited by 0
  8. 2026Multi-View Hierarchical Graph Neural Network for Sketch-Based 3D Shape Retrievalcited by 0
  9. 2026Diff-SBSR: Learning Multimodal Feature-Enhanced Diffusion Models for Zero-Shot Sketch-Based 3D Shape Retrievalcited by 0