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WUSL–SOD: Joint weakly supervised, unsupervised and supervised learning for salient object detection
Deep learning methods for salient object detection (SOD) have been studied actively and promisingly. However, it is still challenging for the studies...
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Weakly supervised pathological whole slide image classification based on contrastive learning
In the context of dealing with limited annotated data, this paper introduces a weakly supervised whole slide image (WSI) classification approach...
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Weakly supervised learning based bone abnormality detection from musculoskeletal x-rays
Accurate localization of abnormalities within X-ray images is of the utmost importance for arriving at the correct diagnosis. Weakly supervised...
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Learning Reliable Dense Pseudo-Labels for Point-Level Weakly-Supervised Action Localization
Point-level weakly-supervised temporal action localization aims to accurately recognize and localize action segments in untrimmed videos, using only...
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Learning from ambiguous labels for X-Ray security inspection via weakly supervised correction
X-ray security inspection has been dominated by supervised learning detectors for several years. The extreme angles, overlap** occlusion, and...
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Weakly supervised target detection based on spatial attention
Due to the lack of annotations in target bounding boxes, most methods for weakly supervised target detection transform the problem of object...
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Bi-calibration Networks for Weakly-Supervised Video Representation Learning
The leverage of large volumes of web videos paired with the query (short phrase for searching the video) or surrounding text (long textual...
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Credible Dual-Expert Learning for Weakly Supervised Semantic Segmentation
Great progress has been witnessed for weakly supervised semantic segmentation, which aims to segment objects without dense pixel annotations. Most...
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Weakly-supervised video anomaly detection via temporal resolution feature learning
AbstractWeakly supervised video anomaly detection (WS-VAD) is often formulated as a multiple instance learning (MIL) problem. Snippet-level anomaly...
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Weakly Supervised Object Detection Based on Active Learning
Weakly supervised object detection which reduces the need for strong supersivison during training has recently made significant achievements....
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Salient-aware multiple instance learning optimized network for weakly supervised object detection
In recent years, weakly supervised object detection network has achieved great development. However, due to the lack of bounding box supervision, the...
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Active self-training for weakly supervised 3D scene semantic segmentation
Since the preparation of labeled data for training semantic segmentation networks of point clouds is a time-consuming process, weakly supervised...
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Category-Aware Saliency Enhance Learning Based on CLIP for Weakly Supervised Salient Object Detection
Weakly supervised salient object detection (SOD) using image-level category labels has been proposed to reduce the annotation cost of pixel-level...
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Deep reinforcement learning for data-efficient weakly supervised business process anomaly detection
The detection of anomalous behavior in business process data is a crucial task for preventing failures that may jeopardize the performance of any...
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Pairwise-Pixel Self-Supervised and Superpixel-Guided Prototype Contrastive Loss for Weakly Supervised Semantic Segmentation
Semantic segmentation plays an important role in many fields because of its powerful ability to classify each pixel efficiently and accurately, but...
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Spiking Reinforcement Learning for Weakly-Supervised Anomaly Detection
Weakly-supervised Anomaly Detection (AD) has achieved significant performance improvement compared to unsupervised methods by harnessing very little...
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Reliability-Adaptive Consistency Regularization for Weakly-Supervised Point Cloud Segmentation
Weakly-supervised point cloud segmentation with extremely limited labels is highly desirable to alleviate the expensive costs of collecting densely...
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Explored seeds generation for weakly supervised semantic segmentation
Weakly supervised semantic segmentation with only image-level labels is an essential application since it reduces the considerable human effort to...
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Weakly supervised graph learning for action recognition in untrimmed video
Action recognition in real-world scenarios is a challenging task which involves the action localization and classification for untrimmed video. Since...
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Improving weakly supervised phrase grounding via visual representation contextualization with contrastive learning
Weakly supervised phrase grounding aims to map the phrases in an image caption to the objects appearing in the image under the supervision of...
