Papers Weakly Supervised Object Detection
“Weakly Supervised Object Detection” 태그가 달린 논문 144편 · 필터 해제
Dual-Thresholded Heatmap-Guided Proposal Clustering and Negative Certainty Supervision with Enhanced Base Network for Weakly Supervised Object Detection
Weakly supervised object detection (WSOD) has attracted significant attention in recent years, as it does not require box-level annotations. State-of-the-art methods generally adopt a multi-module network, which employs …
Weakly Supervised Object DetectionWeakly Supervised Virus Capsid Detection with Image-Level Annotations in Electron Microscopy Images
Current state-of-the-art methods for object detection rely on annotated bounding boxes of large data sets for training. However, obtaining such annotations is expensive and can require up to hundreds of hours of manual l…
Weakly Supervised Object DetectionClass Agnostic Instance-level Descriptor for Visual Instance Search
Despite the great success of the deep features in content-based image retrieval, the visual instance search remains challenging due to the lack of effective instance level feature representation. Supervised or weakly sup…
Content-Based Image RetrievalImage RetrievalInstance SearchObject+3Self-Classification Enhancement and Correction for Weakly Supervised Object Detection
In recent years, weakly supervised object detection (WSOD) has attracted much attention due to its low labeling cost. The success of recent WSOD models is often ascribed to the two-stage multi-class classification (MCC) …
Binary ClassificationClassificationMulti-class ClassificationMultiple Instance Learning+3Enhancing Weakly-Supervised Object Detection on Static Images through (Hallucinated) Motion
While motion has garnered attention in various tasks, its potential as a modality for weakly-supervised object detection (WSOD) in static images remains unexplored. Our study introduces an approach to enhance WSOD method…
Objectobject-detectionObject DetectionRepresentation Learning+1Weakly Supervised Object Detection for Automatic Tooth-marked Tongue Recognition
Tongue diagnosis in Traditional Chinese Medicine (TCM) is a crucial diagnostic method that can reflect an individual's health status. Traditional methods for identifying tooth-marked tongues are subjective and inconsiste…
DiagnosticMultiple Instance Learningobject-detectionObject Detection+1Disentangling spatio-temporal knowledge for weakly supervised object detection and segmentation in surgical video
Weakly supervised video object segmentation (WSVOS) enables the identification of segmentation maps without requiring an extensive training dataset of object masks, relying instead on coarse video labels indicating objec…
DisentanglementKnowledge DistillationObjectobject-detection+6HUWSOD: Holistic Self-training for Unified Weakly Supervised Object Detection
Most WSOD methods rely on traditional object proposals to generate candidate regions and are confronted with unstable training, which easily gets stuck in a poor local optimum. In this paper, we introduce a unified, high…
Objectobject-detectionObject DetectionWeakly Supervised Object DetectionSmart Feature is What You Need
Lack of shape guidance and label jitter caused by information deficiency of weak label are the main problems in 3D weakly-supervised object detection. Current weakly-supervised models often use heuristics or assumptions …
object-detectionObject DetectionWeakly Supervised Object DetectionNegative Prototypes Guided Contrastive Learning for WSOD
Weakly Supervised Object Detection (WSOD) with only image-level annotation has recently attracted wide attention. Many existing methods ignore the inter-image relationship of instances which share similar characteristics…
Contrastive Learningobject-detectionObject DetectionPseudo Label+1Sparse Generation: Making Pseudo Labels Sparse for Point Weakly Supervised Object Detection on Low Data Volume
Existing pseudo label generation methods for point weakly supervised object detection are inadequate in low data volume and dense object detection tasks. We consider the generation of weakly supervised pseudo labels as t…
Dense Object Detectionobject-detectionObject DetectionPseudo Label+1WeakSAM: Segment Anything Meets Weakly-supervised Instance-level Recognition
Weakly supervised visual recognition using inexact supervision is a critical yet challenging learning problem. It significantly reduces human labeling costs and traditionally relies on multi-instance learning and pseudo-…
Image-level Supervised Instance Segmentationobject-detectionObject DetectionSegmentation+2Weakly Supervised Object Detection in Chest X-Rays with Differentiable ROI Proposal Networks and Soft ROI Pooling
Weakly supervised object detection (WSup-OD) increases the usefulness and interpretability of image classification algorithms without requiring additional supervision. The successes of multiple instance learning in this …
image-classificationImage ClassificationMultiple Instance Learningobject-detection+2Weakly Supervised Open-Vocabulary Object Detection
Despite weakly supervised object detection (WSOD) being a promising step toward evading strong instance-level annotations, its capability is confined to closed-set categories within a single training dataset. In this pap…
AttributeNovel ConceptsObjectobject-detection+6LEOD: Label-Efficient Object Detection for Event Cameras
Object detection with event cameras benefits from the sensor's low latency and high dynamic range. However, it is costly to fully label event streams for supervised training due to their high temporal resolution. To redu…
Event-based visionObject DetectionSemi-Supervised Object DetectionWeakly Supervised Object DetectionIdentifying Light-curve Signals with a Deep Learning Based Object Detection Algorithm. II. A General Light Curve Classification Framework
Vast amounts of astronomical photometric data are generated from various projects, requiring significant effort to identify variable stars and other object classes. In light of this, a general, widely applicable classifi…
Anomaly DetectionConformal Predictionobject-detectionObject Detection+1A Weakly Supervised Learning Method for Cell Detection and Tracking Using Incomplete Initial Annotations
The automatic detection of cells in microscopy image sequences is a significant task in biomedical research. However, routine microscopy images with cells, which are taken during the process whereby constant division and…
Cell DetectionCell TrackingWeakly-supervised LearningWeakly Supervised Object DetectionText-image Alignment for Diffusion-based Perception
Diffusion models are generative models with impressive text-to-image synthesis capabilities and have spurred a new wave of creative methods for classical machine learning tasks. However, the best way to harness the perce…
Depth EstimationImage GenerationMonocular Depth Estimationobject-detection+3ALWOD: Active Learning for Weakly-Supervised Object Detection
Object detection (OD), a crucial vision task, remains challenged by the lack of large training datasets with precise object localization labels. In this work, we propose ALWOD, a new framework that addresses this problem…
Active LearningObjectobject-detectionObject Detection+3Gall Bladder Cancer Detection from US Images with Only Image Level Labels
Automated detection of Gallbladder Cancer (GBC) from Ultrasound (US) images is an important problem, which has drawn increased interest from researchers. However, most of these works use difficult-to-acquire information …
Diagnosticimage-classificationImage ClassificationObject+3