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Dense RepPoints: Representing Visual Objects with Dense Point Sets

arXiv 1912.11473 ↗First posted 24 Dec 2019cs.CVcited by 16

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Abstract (arXiv)

We present a new object representation, called Dense RepPoints, that utilizes a large set of points to describe an object at multiple levels, including both box level and pixel level. Techniques are proposed to efficiently process these dense points, maintaining near-constant complexity with increasing point numbers. Dense RepPoints is shown to represent and learn object segments well, with the use of a novel distance transform sampling method combined with set-to-set supervision. The distance transform sampling combines the strengths of contour and grid representations, leading to performance that surpasses counterparts based on contours or grids. Code is available at urlhttps://github.com/justimyhxu/Dense-RepPoints.

Key facts. Cited by 16 papers in the map (data through 14 Oct 2026). First posted on arXiv 24 Dec 2019.

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Citing papers per year: 2021: 8; 2022: 6; 2023: 1; 2024: 1.

16 papers.

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  1. 2021End-to-End Semi-Supervised Object Detection with Soft Teachercited by 316
  2. 2021Probabilistic two-stage detectioncited by 130
  3. 2021Oriented RepPoints for Aerial Object Detectioncited by 102
  4. 2022Sparse Instance Activation for Real-Time Instance Segmentationcited by 63
  5. 2021S3: Neural Shape, Skeleton, and Skinning Fields for 3D Human Modelingcited by 59
  6. 2023All in Tokens: Unifying Output Space of Visual Tasks via Soft Tokencited by 52
  7. 2021Differentiable Multi-Granularity Human Representation Learning for Instance-Aware Human Semantic Parsingcited by 31
  8. 2022E2EC: An End-to-End Contour-based Method for High-Quality High-Speed Instance Segmentationcited by 27
  9. 2022Towards Domain Generalization in Object Detectioncited by 16
  10. 2021VideoClick: Video Object Segmentation with a Single Clickcited by 8
  11. 2022PointScatter: Point Set Representation for Tubular Structure Extractioncited by 8
  12. 2021NAS-FCOS: Efficient Search for Object Detection Architecturescited by 6
4 more
  1. 2022Growing Instance Mask on Leafcited by 1
  2. 2021FourierMask: Instance Segmentation using Fourier Mapping in Implicit Neural Networkscited by 0
  3. 2022Selective Multi-Scale Learning for Object Detectioncited by 0
  4. 2024AdaContour: Adaptive Contour Descriptor with Hierarchical Representationcited by 0