mlsanityData to 7 Oct 2026

MT-ORL: Multi-Task Occlusion Relationship Learning

arXiv 2108.05722 ↗First posted 12 Aug 2021cs.CV cs.LGcited by 4

Not on the map. Why?

Abstract (arXiv)

Retrieving occlusion relation among objects in a single image is challenging due to sparsity of boundaries in image. We observe two key issues in existing works: firstly, lack of an architecture which can exploit the limited amount of coupling in the decoder stage between the two subtasks, namely occlusion boundary extraction and occlusion orientation prediction, and secondly, improper representation of occlusion orientation. In this paper, we propose a novel architecture called Occlusion-shared and Path-separated Network (OPNet), which solves the first issue by exploiting rich occlusion cues in shared high-level features and structured spatial information in task-specific low-level features. We then design a simple but effective orthogonal occlusion representation (OOR) to tackle the second issue. Our method surpasses the state-of-the-art methods by 6.1%/8.3% Boundary-AP and 6.5%/10% Orientation-AP on standard PIOD/BSDS ownership datasets. Code is available at https://github.com/fengpanhe/MT-ORL.

Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). Builds on 17 of its 38 references that are in the map. First posted on arXiv 12 Aug 2021.

Builds on

17 of 38 references.

References · 17

  1. 2015Deep Residual Learning for Image Recognitioncited by 51,809
  2. 2019EfficientDet: Scalable and Efficient Object Detectioncited by 1,018
  3. 2015Holistically-Nested Edge Detectioncited by 590
  4. 2018Bag of Tricks for Image Classification with Convolutional Neural Networkscited by 430
  5. 2020Multi-scale Interactive Network for Salient Object Detectioncited by 212
  6. 2021Deep Occlusion-Aware Instance Segmentation with Overlapping BiLayerscited by 104
  7. 2015Semantic Amodal Segmentationcited by 102
  8. 2020Self-Supervised Scene De-occlusioncited by 96
  9. 2019SharpNet: Fast and Accurate Recovery of Occluding Contours in Monocular Depth Estimationcited by 59
  10. 2020Predicting Sharp and Accurate Occlusion Boundaries in Monocular Depth Estimation Using Displacement Fieldscited by 40
  11. 2019Occlusion-shared and Feature-separated Network for Occlusion Relationship Reasoningcited by 16
  12. 2015Monocular Object Instance Segmentation and Depth Ordering with CNNscited by 14
5 more
  1. 2015Affinity CNN: Learning Pixel-Centric Pairwise Relations for Figure/Ground Embeddingcited by 9
  2. 2020Pixel-Pair Occlusion Relationship Map(P2ORM): Formulation, Inference & Applicationcited by 8
  3. 2018DOOBNet: Deep Object Occlusion Boundary Detection from an Imagecited by 7
  4. 2015DOC: Deep OCclusion Estimation From a Single Imagecited by 6
  5. 2019Context-Constrained Accurate Contour Extraction for Occlusion Edge Detectioncited by 2

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 1; 2023: 0; 2024: 1; 2025: 1; 2026: 1.

4 papers.

  1. 2024Interactive Occlusion Boundary Estimation through Exploitation of Synthetic Datacited by 2
  2. 2025Occlusion Boundary and Depth: Mutual Enhancement via Multi-Task Learningcited by 1
  3. 2022Detection Selection Algorithm: A Likelihood based Optimization Method to Perform Post Processing for Object Detectioncited by 0
  4. 2026RealOOB: A Definition-Consistent Real-World Oriented Occlusion Boundary Benchmarkcited by 0