Fast Interactive Object Annotation with Curve-GCN
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Abstract (arXiv)
Manually labeling objects by tracing their boundaries is a laborious process. In Polygon-RNN++ the authors proposed Polygon-RNN that produces polygonal annotations in a recurrent manner using a CNN-RNN architecture, allowing interactive correction via humans-in-the-loop. We propose a new framework that alleviates the sequential nature of Polygon-RNN, by predicting all vertices simultaneously using a Graph Convolutional Network (GCN). Our model is trained end-to-end. It supports object annotation by either polygons or splines, facilitating labeling efficiency for both line-based and curved objects. We show that Curve-GCN outperforms all existing approaches in automatic mode, including the powerful PSP-DeepLab and is significantly more efficient in interactive mode than Polygon-RNN++. Our model runs at 29.3ms in automatic, and 2.6ms in interactive mode, making it 10x and 100x faster than Polygon-RNN++.
Key facts. Cited by 95 papers in the map (data through 7 Oct 2026). First posted on arXiv 16 Mar 2019.
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Citing papers per year: 2021: 28; 2022: 21; 2023: 17; 2024: 8; 2025: 12; 2026: 9.
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50 most cited of 95 All 95 (JSON)
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- 2024DiffusionNOCS: Managing Symmetry and Uncertainty in Sim2Real Multi-Modal Category-level Pose Estimation20 Feb 2024
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- 2026Topologically Consistent Agricultural Parcel Vectorization with Semantic-Guided Diffusion and Topology-Aware Polygonization7 Sep 2026
- 2025LDPoly: Latent Diffusion for Polygonal Road Outline Extraction in Large-Scale Topographic Mapping29 Apr 2025
- 2023DiffuMask: Synthesizing Images with Pixel-level Annotations for Semantic Segmentation Using Diffusion Models21 Mar 2023
- 2021SegDiff: Image Segmentation with Diffusion Probabilistic Models1 Dec 2021
- 2021KITTI-360: A Novel Dataset and Benchmarks for Urban Scene Understanding in 2D and 3Dcited by 570
- 2021Deep Marching Tetrahedra: a Hybrid Representation for High-Resolution 3D Shape Synthesiscited by 459
- 2022MapTR: Structured Modeling and Learning for Online Vectorized HD Map Constructioncited by 311
- 2023MapTRv2: An End-to-End Framework for Online Vectorized HD Map Constructioncited by 192
- 2022Panoptic NeRF: 3D-to-2D Label Transfer for Panoptic Urban Scene Segmentationcited by 152
- 2021Offboard 3D Object Detection from Point Cloud Sequencescited by 144
- 2022EPIC-KITCHENS VISOR Benchmark: VIdeo Segmentations and Object Relationscited by 139
- 2022BigDatasetGAN: Synthesizing ImageNet with Pixel-wise Annotationscited by 99
- 2023Adaptive Shells for Efficient Neural Radiance Field Renderingcited by 69
- 2021Graph-Based Deep Learning for Medical Diagnosis and Analysis: Past, Present and Futurecited by 67
- 2021Adaptive Boundary Proposal Network for Arbitrary Shape Text Detectioncited by 47
- 2021Auto4D: Learning to Label 4D Objects from Sequential Point Cloudscited by 42
12 most cited of 88 All 88 (JSON)
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- 2026ODE-Based Transformer Decoders for Iterative Sign Language Translation11 Aug 2026
- 2026PolyBuild: An End-to-End Method for Polygonal Building Contour Extraction from High-Resolution Remote Sensing Images8 Jun 2026
- 2026AFUN: Towards an Affordance Foundation Model for Functionality Understanding1 Jun 2026
- 2026Clore: Interactive Pathology Image Segmentation with Click-based Local Refinement29 Mar 2026
- 2026Mask-HybridGNet: Graph-based segmentation with emergent anatomical correspondence from pixel-level supervision24 Feb 2026
- 2025Walk the Lines 2: Contour Tracking for Detailed Segmentation7 Nov 2025
- 2025HoliTracer: Holistic Vectorization of Geographic Objects from Large-Size Remote Sensing Imagery22 Jul 2025
- 2025MARL-MambaContour: Unleashing Multi-Agent Deep Reinforcement Learning for Active Contour Optimization in Medical Image Segmentation23 Jun 2025
- 2025Interactive Instance Annotation with Siamese Networks6 May 2025
- 2025RefCut: Interactive Segmentation with Reference Guidance22 Mar 2025
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