A comprehensive survey on segment anything model for vision and beyond
Artificial intelligence (AI) is evolving towards artificial general intelligence, which refers to the
ability of an AI system to perform a wide range of tasks and exhibit a level of intelligence …
ability of an AI system to perform a wide range of tasks and exhibit a level of intelligence …
Weakly-supervised concealed object segmentation with sam-based pseudo labeling and multi-scale feature grouping
Abstract Weakly-Supervised Concealed Object Segmentation (WSCOS) aims to segment
objects well blended with surrounding environments using sparsely-annotated data for …
objects well blended with surrounding environments using sparsely-annotated data for …
Rethinking the learning paradigm for dynamic facial expression recognition
Abstract Dynamic Facial Expression Recognition (DFER) is a rapidly developing field that
focuses on recognizing facial expressions in video format. Previous research has …
focuses on recognizing facial expressions in video format. Previous research has …
A weakly supervised learning framework for salient object detection via hybrid labels
Fully-supervised salient object detection (SOD) methods have made great progress, but
such methods often rely on a large number of pixel-level annotations, which are time …
such methods often rely on a large number of pixel-level annotations, which are time …
Referring image segmentation using text supervision
Abstract Existing Referring Image Segmentation (RIS) methods typically require expensive
pixel-level or box-level annotations for supervision. In this paper, we observe that the …
pixel-level or box-level annotations for supervision. In this paper, we observe that the …
Dpcnet: Dual path multi-excitation collaborative network for facial expression representation learning in videos
Current works of facial expression learning in video consume significant computational
resources to learn spatial channel feature representations and temporal relationships. To …
resources to learn spatial channel feature representations and temporal relationships. To …
Weakly-supervised camouflaged object detection with scribble annotations
Existing camouflaged object detection (COD) methods rely heavily on large-scale datasets
with pixel-wise annotations. However, due to the ambiguous boundary, annotating …
with pixel-wise annotations. However, due to the ambiguous boundary, annotating …
Robust perception and precise segmentation for scribble-supervised rgb-d saliency detection
This paper proposes a scribble-based weakly supervised RGB-D salient object detection
(SOD) method to relieve the annotation burden from pixel-wise annotations. In view of the …
(SOD) method to relieve the annotation burden from pixel-wise annotations. In view of the …
Mutual information regularization for weakly-supervised RGB-D salient object detection
In this paper, we present a weakly-supervised RGB-D salient object detection model via
scribble supervision. Specifically, as a multimodal learning task, we focus on effective …
scribble supervision. Specifically, as a multimodal learning task, we focus on effective …
Deep hypersphere feature regularization for weakly supervised RGB-D salient object detection
We propose a weakly supervised approach for salient object detection from multi-modal
RGB-D data. Our approach only relies on labels from scribbles, which are much easier to …
RGB-D data. Our approach only relies on labels from scribbles, which are much easier to …