Federated learning with label distribution skew via logits calibration
Traditional federated optimization methods perform poorly with heterogeneous data (ie,
accuracy reduction), especially for highly skewed data. In this paper, we investigate the label …
accuracy reduction), especially for highly skewed data. In this paper, we investigate the label …
Rethinking the learning paradigm for dynamic facial expression recognition
Abstract Dynamic Facial Expression Recognition (DFER) is a rapidly develo** field that
focuses on recognizing facial expressions in video format. Previous research has …
focuses on recognizing facial expressions in video format. Previous research has …
Global-and-local collaborative learning for co-salient object detection
The goal of co-salient object detection (CoSOD) is to discover salient objects that commonly
appear in a query group containing two or more relevant images. Therefore, how to …
appear in a query group containing two or more relevant images. Therefore, how to …
HRTransNet: HRFormer-driven two-modality salient object detection
The High-Resolution Transformer (HRFormer) can maintain high-resolution representation
and share global receptive fields. It is friendly towards salient object detection (SOD) in …
and share global receptive fields. It is friendly towards salient object detection (SOD) in …
Learning implicit class knowledge for RGB-D co-salient object detection with transformers
RGB-D co-salient object detection aims to segment co-occurring salient objects when given
a group of relevant images and depth maps. Previous methods often adopt separate …
a group of relevant images and depth maps. Previous methods often adopt separate …
Tcnet: Co-salient object detection via parallel interaction of transformers and cnns
Y Ge, Q Zhang, TZ **ang, C Zhang… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
The purpose of co-salient object detection (CoSOD) is to detect the salient objects that co-
occur in a group of relevant images. CoSOD has been significantly prospered by recent …
occur in a group of relevant images. CoSOD has been significantly prospered by recent …
Memory-aided contrastive consensus learning for co-salient object detection
Co-salient object detection (CoSOD) aims at detecting common salient objects within a
group of relevant source images. Most of the latest works employ the attention mechanism …
group of relevant source images. Most of the latest works employ the attention mechanism …
Attack can benefit: An adversarial approach to recognizing facial expressions under noisy annotations
Abstract The real-world Facial Expression Recognition (FER) datasets usually exhibit
complex scenarios with coupled noise annotations and imbalanced classes distribution …
complex scenarios with coupled noise annotations and imbalanced classes distribution …
Toward stable co-saliency detection and object co-segmentation
In this paper, we present a novel model for simultaneous stable co-saliency detection
(CoSOD) and object co-segmentation (CoSEG). To detect co-saliency (segmentation) …
(CoSOD) and object co-segmentation (CoSEG). To detect co-saliency (segmentation) …
Re-thinking the relations in co-saliency detection
Co-salient object detection (CoSOD) aims to detect common salient objects sharing the
same attributes in an image group. The key issue of CoSOD is how to model the inter …
same attributes in an image group. The key issue of CoSOD is how to model the inter …