SOTAVerified

Object Detection

Papers

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Showing 7451–7500 of 10957 papers

TitleStatusHype
BandRe: Rethinking Band-Pass Filters for Scale-Wise Object Detection Evaluation—0
A multitask deep learning model for real-time deployment in embedded systems—0
Learning a Layout Transfer Network for Context Aware Object Detection—0
Positive-Unlabeled Data Purification in the Wild for Object Detection—0
Learning a Domain Classifier Bank for Unsupervised Adaptive Object Detection—0
Postdisaster image-based damage detection and repair cost estimation of reinforced concrete buildings using dual convolutional neural networks—0
Poster: Making Edge-assisted LiDAR Perceptions Robust to Lossy Point Cloud Compression—0
Post-hoc Models for Performance Estimation of Machine Learning Inference—0
BAM: Box Abstraction Monitors for Real-time OoD Detection in Object Detection—0
Post-training Quantization with Multiple Points: Mixed Precision without Mixed Precision—0
Learning 3D Perception from Others' Predictions—0
A Multispectral Automated Transfer Technique (MATT) for machine-driven image labeling utilizing the Segment Anything Model (SAM)—0
Learned Two-Plane Perspective Prior based Image Resampling for Efficient Object Detection—0
Balancing Stability and Plasticity in Pretrained Detector: A Dual-Path Framework for Incremental Object Detection—0
Learned Multimodal Compression for Autonomous Driving—0
Learned Fusion: 3D Object Detection using Calibration-Free Transformer Feature Fusion—0
Learned Enrichment of Top-View Grid Maps Improves Object Detection—0
Learned Disentangled Latent Representations for Scalable Image Coding for Humans and Machines—0
DenSe-AdViT: A novel Vision Transformer for Dense SAR Object Detection—0
Balancing Privacy and Action Performance: A Penalty-Driven Approach to Image Anonymization—0
A Multi-purpose Realistic Haze Benchmark with Quantifiable Haze Levels and Ground Truth—0
A 3D Object Detection and Pose Estimation Pipeline Using RGB-D Images—0
Learnable Histogram: Statistical Context Features for Deep Neural Networks—0
Learnable Companding Quantization for Accurate Low-bit Neural Networks—0
LEAP:D - A Novel Prompt-based Approach for Domain-Generalized Aerial Object Detection—0
Practical Implementation of RIS-Aided Spectrum Sensing: A Deep Learning-Based Solution—0
Sparsely-gated Mixture-of-Expert Layers for CNN Interpretability—0
LEAF + AIO: Edge-Assisted Energy-Aware Object Detection for Mobile Augmented Reality—0
Leadership Assessment in Pediatric Intensive Care Unit Team Training—0
Precise Box Score: Extract More Information from Datasets to Improve the Performance of Face Detection—0
LDD: A Dataset for Grape Diseases Object Detection and Instance Segmentation—0
Precise Payload Delivery via Unmanned Aerial Vehicles: An Approach Using Object Detection Algorithms—0
Precise Single-stage Detector—0
Are we Missing Confidence in Pseudo-LiDAR Methods for Monocular 3D Object Detection?—0
Precision and Adaptability of YOLOv5 and YOLOv8 in Dynamic Robotic Environments—0
PreDet: Large-Scale Weakly Supervised Pre-Training for Detection—0
Cut-and-Paste Dataset Generation for Balancing Domain Gaps in Object Instance Detection—0
LCV2: An Efficient Pretraining-Free Framework for Grounded Visual Question Answering—0
LCV2I: Communication-Efficient and High-Performance Collaborative Perception Framework with Low-Resolution LiDAR—0
Demystifying Contrastive Self-Supervised Learning: Invariances, Augmentations and Dataset Biases—0
Balance-Oriented Focal Loss with Linear Scheduling for Anchor Free Object Detection—0
LCDet: Low-Complexity Fully-Convolutional Neural Networks for Object Detection in Embedded Systems—0
Predictive Ensemble Learning with Application to Scene Text Detection—0
LC3Net: Ladder context correlation complementary network for salient object detection—0
Predictive Uncertainty in Deep Object Detectors: Estimation and Evaluation—0
Demystifying Catastrophic Forgetting in Two-Stage Incremental Object Detector—0
Preprocessing Enhanced Image Compression for Machine Vision—0
Prescriptive and Descriptive Approaches to Machine-Learning Transparency—0
A Generic Shared Attention Mechanism for Various Backbone Neural Networks—0
Layer-wise Customized Weak Segmentation Block and AIoU Loss for Accurate Object Detection—0
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All datasetsCOCO test-devCOCO minivalCOCO-OCOCO 2017 valPASCAL VOC 2007COCO 2017CrowdHuman (full body)CPPE-5LVIS v1.0 valManga109-s 15testPKU-DDD17-CarWaymo 2D detection all_ns f0val

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Co-DETRbox mAP66—Unverified
2InternImage-H (M3I Pre-training)box mAP65.5—Unverified
3M3I Pre-training (InternImage-H)box mAP65.4—Unverified
4MoCaEbox mAP65.1—Unverified
5Co-DETR (Swin-L)box mAP64.8—Unverified
6Focal-Stable-DINO (Focal-Huge, no TTA)box mAP64.8—Unverified
7EVAbox mAP64.7—Unverified
8Group DETR v2box mAP64.5—Unverified
9FocalNet-H (DINO)box mAP64.4—Unverified
10InternImage-XLbox mAP64.3—Unverified