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Region Proposal

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Showing 276–300 of 373 papers

TitleStatusHype
Named Entity Recognition in the Style of Object Detection—0
Non-local RoI for Cross-Object Perception—0
N-RPN: Hard Example Learning for Region Proposal Networks—0
Object-Extent Pooling for Weakly Supervised Single-Shot Localization—0
One for All: One-stage Referring Expression Comprehension with Dynamic Reasoning—0
Online Pseudo-Label Unified Object Detection for Multiple Datasets Training—0
Open-Set Object Detection Using Classification-free Object Proposal and Instance-level Contrastive Learning—0
Optimizing the Trade-off between Single-Stage and Two-Stage Object Detectors using Image Difficulty Prediction—0
OralXrays-9: Towards Hospital-Scale Panoramic X-ray Anomaly Detection via Personalized Multi-Object Query-Aware Mining—0
Panoptic Segmentation with an End-to-End Cell R-CNN for Pathology Image Analysis—0
Parts4Feature: Learning 3D Global Features from Generally Semantic Parts in Multiple Views—0
Patch Refinement -- Localized 3D Object Detection—0
Pattern Spotting and Image Retrieval in Historical Documents using Deep Hashing—0
PIE-NET: Parametric Inference of Point Cloud Edges—0
Pixel and Feature Level Based Domain Adaption for Object Detection in Autonomous Driving—0
Polyp-artifact relationship analysis using graph inductive learned representations—0
Pose-Aware Instance Segmentation Framework from Cone Beam CT Images for Tooth Segmentation—0
Proposal-based Few-shot Sound Event Detection for Speech and Environmental Sounds with Perceivers—0
Proposal-free Network for Instance-level Object Segmentation—0
ProteinRPN: Towards Accurate Protein Function Prediction with Graph-Based Region Proposals—0
Prototypical Region Proposal Networks for Few-Shot Localization and Classification—0
Query-Guided Networks for Few-shot Fine-grained Classification and Person Search—0
R^3-Net: A Deep Network for Multi-oriented Vehicle Detection in Aerial Images and Videos—0
Radar-Camera Sensor Fusion for Joint Object Detection and Distance Estimation in Autonomous Vehicles—0
Radar-Lidar Fusion for Object Detection by Designing Effective Convolution Networks—0
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