IS THE U-NET DIRECTIONAL-RELATIONSHIP AWARE? - Archive ouverte HAL Access content directly
Conference Papers Year :

IS THE U-NET DIRECTIONAL-RELATIONSHIP AWARE?

(1, 2, 3) , (1, 2, 3) , (4) , (5, 6)
1
2
3
4
5
6

Abstract

CNNs are often assumed to be capable of using contextual information about distinct objects (such as their directional relations) inside their receptive field. However, the nature and limits of this capacity has never been explored in full. We explore a specific type of relationship-directional-using a standard U-Net trained to optimize a cross-entropy loss function for segmentation. We train this network on a pretext segmentation task requiring directional relation reasoning for success and state that, with enough data and a sufficiently large receptive field, it succeeds to learn the proposed task. We further explore what the network has learned by analysing scenarios where the directional relationships are perturbed, and show that the network has learned to reason using these relationships.
Fichier principal
Vignette du fichier
ICIP___Is_the_U_Net_Directional_Relationship_Aware.pdf (772.37 Ko) Télécharger le fichier
Origin : Files produced by the author(s)

Dates and versions

hal-03715361 , version 1 (06-07-2022)

Identifiers

  • HAL Id : hal-03715361 , version 1

Cite

Mateus Riva, Pietro Gori, Florian Yger, Isabelle Bloch. IS THE U-NET DIRECTIONAL-RELATIONSHIP AWARE?. International Conference on Image Processing, Oct 2022, Bordeaux, France. ⟨hal-03715361⟩
186 View
8 Download

Share

Gmail Facebook Twitter LinkedIn More