1 code implementation • 27 Feb 2023 • Rongtao Xu, Changwei Wang, Jiaxi Sun, Shibiao Xu, Weiliang Meng, Xiaopeng Zhang
In addition, to further improve the segmentation accuracy, we design a Variation-aware Refine Module to enhance the local consistency of pseudo-labels by computing pixel-level variation.
Weakly supervised Semantic Segmentation Weakly-Supervised Semantic Segmentation
no code implementations • 17 Jan 2023 • Sen Pei, Jiaxi Sun, Richard Yi Da Xu, Bin Fan, Shiming Xiang, Gaofeng Meng
Generally, existing approaches in dealing with out-of-distribution (OOD) detection mainly focus on the statistical difference between the features of OOD and in-distribution (ID) data extracted by the classifiers.
1 code implementation • 25 Jul 2022 • Sen Pei, Jiaxi Sun, Richard Yi Da Xu, Shiming Xiang, Gaofeng Meng
PoER helps the neural networks to capture label-related features which contain the domain information first in shallow layers and then distills the label-discriminative representations out progressively, enforcing the neural networks to be aware of the characteristic of objects and background which is vital to the generation of domain-invariant features.
no code implementations • 21 May 2022 • Sen Pei, Jiaxi Sun, Xiaopeng Zhang, Gaofeng Meng
Recent studies show that the deep neural networks (DNNs) have achieved great success in various tasks.