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Object Detection

Papers

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Showing 4826–4850 of 10957 papers

TitleStatusHype
TED-Net: Dispersal Attention for Perceiving Interaction Region in Indirectly-Contact HOI DetectionCode0
From Blurry to Brilliant Detection: YOLOv5-Based Aerial Object Detection with Super Resolution—0
UrbanGenAI: Reconstructing Urban Landscapes using Panoptic Segmentation and Diffusion Models—0
Knowledge Graph Driven UAV Cognitive Semantic Communication Systems for Efficient Object Detection—0
PLATE: A perception-latency aware estimator,—0
Towards Complementary Knowledge Distillation for Efficient Dense Image Prediction—0
Deep Learning for Improved Polyp Detection from Synthetic Narrow-Band Imaging—0
AMANet: Advancing SAR Ship Detection with Adaptive Multi-Hierarchical Attention Network—0
Small Language Model Meets with Reinforced Vision Vocabulary—0
Pragmatic Communication in Multi-Agent Collaborative PerceptionCode0
Enhancing Object Detection Performance for Small Objects through Synthetic Data Generation and Proportional Class-Balancing Technique: A Comparative Study in Industrial Scenarios—0
Concealed Object Segmentation with Hierarchical Coherence Modeling—0
A Saliency Enhanced Feature Fusion based multiscale RGB-D Salient Object Detection Network—0
Out-of-Distribution Detection & Applications With Ablated Learned Temperature EnergyCode0
MsSVT++: Mixed-scale Sparse Voxel Transformer with Center Voting for 3D Object Detection—0
Large receptive field strategy and important feature extraction strategy in 3D object detection—0
ANNA: A Deep Learning Based Dataset in Heterogeneous Traffic for Autonomous VehiclesCode0
The State of Computer Vision Research in AfricaCode0
Stability Plasticity Decoupled Fine-tuning For Few-shot end-to-end Object Detection—0
TDC-less Direct Time-of-Flight Imaging Using Spiking Neural Networks—0
Detection of Thermal Events by Semi-Supervised Learning for Tokamak First Wall Safety—0
BadODD: Bangladeshi Autonomous Driving Object Detection Dataset—0
Measuring the Impact of Scene Level Objects on Object Detection: Towards Quantitative Explanations of Detection Decisions—0
One Step Learning, One Step ReviewCode0
M3BUNet: Mobile Mean Max UNet for Pancreas Segmentation on CT-Scans—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