A comprehensive survey on segment anything model for vision and beyond

C Zhang, L Liu, Y Cui, G Huang, W Lin, Y Yang… - arXiv preprint arXiv …, 2023 - arxiv.org
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 …

Weakly-supervised concealed object segmentation with sam-based pseudo labeling and multi-scale feature grouping

C He, K Li, Y Zhang, G Xu, L Tang… - Advances in …, 2024 - proceedings.neurips.cc
Abstract Weakly-Supervised Concealed Object Segmentation (WSCOS) aims to segment
objects well blended with surrounding environments using sparsely-annotated data for …

Rethinking the learning paradigm for dynamic facial expression recognition

H Wang, B Li, S Wu, S Shen, F Liu… - Proceedings of the …, 2023 - openaccess.thecvf.com
Abstract Dynamic Facial Expression Recognition (DFER) is a rapidly developing field that
focuses on recognizing facial expressions in video format. Previous research has …

A weakly supervised learning framework for salient object detection via hybrid labels

R Cong, Q Qin, C Zhang, Q Jiang… - … on Circuits and …, 2022 - ieeexplore.ieee.org
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 …

Referring image segmentation using text supervision

F Liu, Y Liu, Y Kong, K Xu, L Zhang… - Proceedings of the …, 2023 - openaccess.thecvf.com
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 …

Dpcnet: Dual path multi-excitation collaborative network for facial expression representation learning in videos

Y Wang, Y Sun, W Song, S Gao, Y Huang… - Proceedings of the 30th …, 2022 - dl.acm.org
Current works of facial expression learning in video consume significant computational
resources to learn spatial channel feature representations and temporal relationships. To …

Weakly-supervised camouflaged object detection with scribble annotations

R He, Q Dong, J Lin, RWH Lau - … of the AAAI Conference on Artificial …, 2023 - ojs.aaai.org
Existing camouflaged object detection (COD) methods rely heavily on large-scale datasets
with pixel-wise annotations. However, due to the ambiguous boundary, annotating …

Robust perception and precise segmentation for scribble-supervised rgb-d saliency detection

L Li, J Han, N Liu, S Khan, H Cholakkal… - … on Pattern Analysis …, 2023 - ieeexplore.ieee.org
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 …

Mutual information regularization for weakly-supervised RGB-D salient object detection

A Li, Y Mao, J Zhang, Y Dai - … on Circuits and Systems for Video …, 2023 - ieeexplore.ieee.org
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 …

Deep hypersphere feature regularization for weakly supervised RGB-D salient object detection

Z Liu, M Hayat, H Yang, D Peng… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
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 …