Papers Weakly-supervised Learning
“Weakly-supervised Learning” 태그가 달린 논문 613편 · 필터 해제
Dual‑detector Re‑optimization for Federated Weakly Supervised Video Anomaly Detection Via Adaptive Dynamic Recursive Mapping
Federated weakly supervised video anomaly detection represents a significant advancement in privacy-preserving collaborative learning, enabling distributed clients to train anomaly detectors using only video-level annota…
Anomaly DetectionAnomaly Detection In Surveillance VideosEdge-computingFederated Learning+5Bootstrapping World Models from Dynamics Models in Multimodal Foundation Models
To what extent do vision-and-language foundation models possess a realistic world model (observation $\times$ action $\rightarrow$ observation) and a dynamics model (observation $\times$ observation $\rightarrow$ action)…
Weakly-supervised LearningWeakly-supervised Mamba-Based Mastoidectomy Shape Prediction for Cochlear Implant Surgery Using 3D T-Distribution Loss
Cochlear implant surgery is a treatment for individuals with severe hearing loss. It involves inserting an array of electrodes inside the cochlea to electrically stimulate the auditory nerve and restore hearing sensation…
MambaWeakly-supervised LearningBridging Sign and Spoken Languages: Pseudo Gloss Generation for Sign Language Translation
Sign Language Translation (SLT) aims to map sign language videos to spoken language text. A common approach relies on gloss annotations as an intermediate representation, decomposing SLT into two sub-tasks: video-to-glos…
In-Context LearningLarge Language ModelSign Language TranslationTranslation+1Bronchovascular Tree-Guided Weakly Supervised Learning Method for Pulmonary Segment Segmentation
Pulmonary segment segmentation is crucial for cancer localization and surgical planning. However, the pixel-wise annotation of pulmonary segments is laborious, as the boundaries between segments are indistinguishable in …
AnatomySegmentationWeakly-supervised LearningLearning from Similarity Proportion Loss for Classifying Skeletal Muscle Recovery Stages
Evaluating the regeneration process of damaged muscle tissue is a fundamental analysis in muscle research to measure experimental effect sizes and uncover mechanisms behind muscle weakness due to aging and disease. The c…
Weakly-supervised LearningPartial Label Clustering
Partial label learning (PLL) is a significant weakly supervised learning framework, where each training example corresponds to a set of candidate labels and only one label is the ground-truth label. For the first time, t…
ClusteringConstrained ClusteringGraph LearningPartial Label Learning+1Advancing Arabic Speech Recognition Through Large-Scale Weakly Supervised Learning
Automatic speech recognition (ASR) is crucial for human-machine interaction in diverse applications like conversational agents, industrial robotics, call center automation, and automated subtitling. However, developing h…
Arabic Speech RecognitionAutomatic Speech RecognitionAutomatic Speech Recognition (ASR)speech-recognition+2Ising Models with Hidden Markov Structure: Applications to Probabilistic Inference in Machine Learning
In this paper, we investigate tree-indexed Markov chains (Gibbs measures) defined by a Hamiltonian that couples two Ising layers: hidden spins \(s(x) \in \{\pm 1\}\) and observed spins \(\sigma(x) \in \{\pm 1\}\) on a Ca…
Anomaly DetectionDenoisingWeakly-supervised LearningA Novel Approach to Linking Histology Images with DNA Methylation
DNA methylation is an epigenetic mechanism that regulates gene expression by adding methyl groups to DNA. Abnormal methylation patterns can disrupt gene expression and have been linked to cancer development. To quantify …
Graph Neural NetworkWeakly-supervised Learningwhole slide imagesAudio-driven Gesture Generation via Deviation Feature in the Latent Space
Gestures are essential for enhancing co-speech communication, offering visual emphasis and complementing verbal interactions. While prior work has concentrated on point-level motion or fully supervised data-driven method…
Gesture GenerationVideo GenerationWeakly-supervised LearningLiDAR Remote Sensing Meets Weak Supervision: Concepts, Methods, and Perspectives
LiDAR (Light Detection and Ranging) enables rapid and accurate acquisition of three-dimensional spatial data, widely applied in remote sensing areas such as surface mapping, environmental monitoring, urban modeling, and …
ArticlesWeakly-supervised LearningFG$^2$: Fine-Grained Cross-View Localization by Fine-Grained Feature Matching
We propose a novel fine-grained cross-view localization method that estimates the 3 Degrees of Freedom pose of a ground-level image in an aerial image of the surroundings by matching fine-grained features between the two…
Weakly-supervised LearningDEPT: Deep Extreme Point Tracing for Ultrasound Image Segmentation
Automatic medical image segmentation plays a crucial role in computer aided diagnosis. However, fully supervised learning approaches often require extensive and labor-intensive annotation efforts. To address this challen…
Image SegmentationMedical Image SegmentationSemantic SegmentationWeakly-supervised LearningLearning from Noisy Labels with Contrastive Co-Transformer
Deep learning with noisy labels is an interesting challenge in weakly supervised learning. Despite their significant learning capacity, CNNs have a tendency to overfit in the presence of samples with noisy labels. Allevi…
Learning with noisy labelsWeakly-supervised LearningLocalEscaper: A Weakly-supervised Framework with Regional Reconstruction for Scalable Neural TSP Solvers
Neural solvers have shown significant potential in solving the Traveling Salesman Problem (TSP), yet current approaches face significant challenges. Supervised learning (SL)-based solvers require large amounts of high-qu…
Reinforcement Learning (RL)Traveling Salesman ProblemWeakly-supervised LearningRobust Partial-Label Learning by Leveraging Class Activation Values
Real-world training data is often noisy; for example, human annotators assign conflicting class labels to the same instances. Partial-label learning (PLL) is a weakly supervised learning paradigm that allows training cla…
Partial Label LearningWeakly-supervised LearningQMaxViT-Unet+: A Query-Based MaxViT-Unet with Edge Enhancement for Scribble-Supervised Segmentation of Medical Images
The deployment of advanced deep learning models for medical image segmentation is often constrained by the requirement for extensively annotated datasets. Weakly-supervised learning, which allows less precise labels, has…
DecoderImage SegmentationMedical Image AnalysisMedical Image Segmentation+2Realistic Evaluation of Deep Partial-Label Learning Algorithms
Partial-label learning (PLL) is a weakly supervised learning problem in which each example is associated with multiple candidate labels and only one is the true label. In recent years, many deep PLL algorithms have been …
Model SelectionPartial Label LearningWeakly-supervised LearningPUATE: Efficient Average Treatment Effect Estimation from Treated (Positive) and Unlabeled Units
The estimation of average treatment effects (ATEs), defined as the difference in expected outcomes between treatment and control groups, is a central topic in causal inference. This study develops semiparametric efficien…
Causal InferenceWeakly-supervised Learning