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PAD-Net: Multi-Tasks Guided Prediction-and-Distillation Network for Simultaneous Depth Estimation and Scene Parsing

arXiv 1805.04409 ↗First posted 11 May 2018cs.CVcited by 224

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Abstract (arXiv)

Depth estimation and scene parsing are two particularly important tasks in visual scene understanding. In this paper we tackle the problem of simultaneous depth estimation and scene parsing in a joint CNN. The task can be typically treated as a deep multi-task learning problem [42]. Different from previous methods directly optimizing multiple tasks given the input training data, this paper proposes a novel multi-task guided prediction-and-distillation network (PAD-Net), which first predicts a set of intermediate auxiliary tasks ranging from low level to high level, and then the predictions from these intermediate auxiliary tasks are utilized as multi-modal input via our proposed multi-modal distillation modules for the final tasks. During the joint learning, the intermediate tasks not only act as supervision for learning more robust deep representations but also provide rich multi-modal information for improving the final tasks. Extensive experiments are conducted on two challenging datasets (i.e. NYUD-v2 and Cityscapes) for both the depth estimation and scene parsing tasks, demonstrating the effectiveness of the proposed approach.

Key facts. Cited by 224 papers in the map (data through 7 Oct 2026). First posted on arXiv 11 May 2018.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 48; 2022: 37; 2023: 48; 2024: 42; 2025: 28; 2026: 21.

224 papers.

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  1. 2021Omnidata: A Scalable Pipeline for Making Multi-Task Mid-Level Vision Datasets from 3D Scanscited by 336
  2. 2021Categorical Depth Distribution Network for Monocular 3D Object Detectioncited by 326
  3. 2024GeoWizard: Unleashing the Diffusion Priors for 3D Geometry Estimation from a Single Imagecited by 283
  4. 2022CMX: Cross-Modal Fusion for RGB-X Semantic Segmentation with Transformerscited by 229
  5. 2021Geometry Uncertainty Projection Network for Monocular 3D Object Detectioncited by 155
  6. 2021Transformer-Based Attention Networks for Continuous Pixel-Wise Predictioncited by 125
  7. 2022P3Depth: Monocular Depth Estimation with a Piecewise Planarity Priorcited by 106
  8. 2022M3ViT: Mixture-of-Experts Vision Transformer for Efficient Multi-task Learning with Model-Accelerator Co-designcited by 97
  9. 2022InvPT: Inverted Pyramid Multi-task Transformer for Dense Scene Understandingcited by 89
  10. 2021Domain Adaptive Semantic Segmentation with Self-Supervised Depth Estimationcited by 80
  11. 2021Leveraging Auxiliary Tasks with Affinity Learning for Weakly Supervised Semantic Segmentationcited by 77
  12. 2022Auto-Lambda: Disentangling Dynamic Task Relationshipscited by 73
38 more
  1. 2021Exploring Relational Context for Multi-Task Dense Predictioncited by 71
  2. 2023iDisc: Internal Discretization for Monocular Depth Estimationcited by 71
  3. 20223D Object Detection from Images for Autonomous Driving: A Surveycited by 66
  4. 2021InverseForm: A Loss Function for Structured Boundary-Aware Segmentationcited by 65
  5. 2024Multi-Task Dense Prediction via Mixture of Low-Rank Expertscited by 58
  6. 2021Fine-grained Semantics-aware Representation Enhancement for Self-supervised Monocular Depth Estimationcited by 55
  7. 20213D-to-2D Distillation for Indoor Scene Parsingcited by 47
  8. 2021EvDistill: Asynchronous Events to End-task Learning via Bidirectional Reconstruction-guided Cross-modal Knowledge Distillationcited by 46
  9. 2023TaskExpert: Dynamically Assembling Multi-Task Representations with Memorial Mixture-of-Expertscited by 45
  10. 2024MTLoRA: A Low-Rank Adaptation Approach for Efficient Multi-Task Learningcited by 44
  11. 2021Adaptive Surface Normal Constraint for Depth Estimationcited by 43
  12. 2021Learning Multiple Dense Prediction Tasks from Partially Annotated Datacited by 42
  13. 2021Active Boundary Loss for Semantic Segmentationcited by 40
  14. 2022Cross-Domain Correlation Distillation for Unsupervised Domain Adaptation in Nighttime Semantic Segmentationcited by 40
  15. 2021Polarized Self-Attention: Towards High-quality Pixel-wise Regressioncited by 39
  16. 2021Meta-Learning Dynamics Forecasting Using Task Inferencecited by 37
  17. 2021Single Image Depth Estimation: An Overviewcited by 35
  18. 2021Cross-modal Consensus Network for Weakly Supervised Temporal Action Localizationcited by 34
  19. 2022Multi-Task Learning with Multi-Query Transformer for Dense Predictioncited by 34
  20. 2021SOSD-Net: Joint Semantic Object Segmentation and Depth Estimation from Monocular imagescited by 33
  21. 2021Learning to Relate Depth and Semantics for Unsupervised Domain Adaptationcited by 32
  22. 2021Dual Transfer Learning for Event-based End-task Prediction via Pluggable Event to Image Translationcited by 31
  23. 2021Learning Scene Structure Guidance via Cross-Task Knowledge Transfer for Single Depth Super-Resolutioncited by 30
  24. 2022Less is More: Consistent Video Depth Estimation with Masked Frames Modelingcited by 30
  25. 2023SA-BEV: Generating Semantic-Aware Bird's-Eye-View Feature for Multi-view 3D Object Detectioncited by 30
  26. 2022Learning with Recoverable Forgettingcited by 29
  27. 2023Prismer: A Vision-Language Model with Multi-Task Expertscited by 28
  28. 2022MGNet: Monocular Geometric Scene Understanding for Autonomous Drivingcited by 27
  29. 2023DeMT: Deformable Mixer Transformer for Multi-Task Learning of Dense Predictioncited by 27
  30. 2022Towards Versatile Embodied Navigationcited by 26
  31. 2023Semantic Image Segmentation: Two Decades of Researchcited by 26
  32. 2021Improving Semi-Supervised and Domain-Adaptive Semantic Segmentation with Self-Supervised Depth Estimationcited by 25
  33. 2022DenseMTL: Cross-task Attention Mechanism for Dense Multi-task Learningcited by 25
  34. 2021Robustness via Cross-Domain Ensemblescited by 23
  35. 2022Universal Representations: A Unified Look at Multiple Task and Domain Learningcited by 23
  36. 2023Edge-MoE: Memory-Efficient Multi-Task Vision Transformer Architecture with Task-level Sparsity via Mixture-of-Expertscited by 23
  37. 2021Semi-supervised Multi-task Learning for Semantics and Depthcited by 22
  38. 2023InvPT++: Inverted Pyramid Multi-Task Transformer for Visual Scene Understandingcited by 22

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