Texture learning domain randomization for domain generalized segmentation
Abstract Deep Neural Networks (DNNs)-based semantic segmentation models trained on a
source domain often struggle to generalize to unseen target domains, ie, a domain gap …
source domain often struggle to generalize to unseen target domains, ie, a domain gap …
Deconfounded Emotion Guidance Sticker Selection with Causal Inference
With the increasing popularity of online social applications, stickers have become common
in online chats. Teaching a model to select the appropriate sticker from a set of candidate …
in online chats. Teaching a model to select the appropriate sticker from a set of candidate …
Semantic self-adaptation: Enhancing generalization with a single sample
The lack of out-of-domain generalization is a critical weakness of deep networks for
semantic segmentation. Previous studies relied on the assumption of a static model, ie, once …
semantic segmentation. Previous studies relied on the assumption of a static model, ie, once …
Causal Invariant Representation Learning Based on Style Intervention Identity Regularization for Remote Sensing Image
Y Zhang, F Liu, J Zhang, H Li - IEEE Geoscience and Remote …, 2025 - ieeexplore.ieee.org
An intelligent understanding model of a remote sensing image will present different visual
representations of the same object in the remote sensing image, under the interference of …
representations of the same object in the remote sensing image, under the interference of …