mlsanityData to 7 Oct 2026

Fractal Pyramid Networks

arXiv 2106.14694 ↗First posted 28 Jun 2021cs.CV cs.AIcited by 2

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Abstract (arXiv)

We propose a new network architecture, the Fractal Pyramid Networks (PFNs) for pixel-wise prediction tasks as an alternative to the widely used encoder-decoder structure. In the encoder-decoder structure, the input is processed by an encoding-decoding pipeline that tries to get a semantic large-channel feature. Different from that, our proposed PFNs hold multiple information processing pathways and encode the information to multiple separate small-channel features. On the task of self-supervised monocular depth estimation, even without ImageNet pretrained, our models can compete or outperform the state-of-the-art methods on the KITTI dataset with much fewer parameters. Moreover, the visual quality of the prediction is significantly improved. The experiment of semantic segmentation provides evidence that the PFNs can be applied to other pixel-wise prediction tasks, and demonstrates that our models can catch more global structure information.

Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 42 of its 47 references that are in the map. First posted on arXiv 28 Jun 2021.

Builds on

42 of 47 references.

References · 42

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30 more
  1. 2018Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentationcited by 3,210
  2. 2016Pyramid Scene Parsing Networkcited by 2,472
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  13. 2016Optical Flow Estimation using a Spatial Pyramid Networkcited by 421
  14. 2019Selective Kernel Networkscited by 401
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  18. 2016FractalNet: Ultra-Deep Neural Networks without Residualscited by 216
  19. 2018Unsupervised Learning of Depth and Ego-Motion from Monocular Video Using 3D Geometric Constraintscited by 179
  20. 2018Depth Prediction Without the Sensors: Leveraging Structure for Unsupervised Learning from Monocular Videoscited by 155
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  24. 2017Semi-Supervised Deep Learning for Monocular Depth Map Predictioncited by 109
  25. 2020Towards Better Generalization: Joint Depth-Pose Learning without PoseNetcited by 85
  26. 2020Blind Video Temporal Consistency via Deep Video Priorcited by 76
  27. 2019Exploiting temporal consistency for real-time video depth estimationcited by 61
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  29. 2019Unsupervised High-Resolution Depth Learning From Videos With Dual Networkscited by 26
  30. 2020Attentional Separation-and-Aggregation Network for Self-supervised Depth-Pose Learning in Dynamic Scenescited by 11

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Citing papers per year: 2023: 2.

2 papers.

  1. 2023X-MLP: A Patch Embedding-Free MLP Architecture for Visioncited by 6
  2. 2023Learning Fractals by Gradient Descentcited by 2