SOTAVerified

Object Detection

Papers

Showing 76100 of 10957 papers

TitleStatusHype
Leadership Assessment in Pediatric Intensive Care Unit Team Training0
Deformable Attention Mechanisms Applied to Object Detection, case of Remote Sensing0
Conformal Object Detection by Sequential Risk Control0
Boosting Domain Incremental Learning: Selecting the Optimal Parameters is All You NeedCode0
Rooms from Motion: Un-posed Indoor 3D Object Detection as Localization and Mapping0
FMG-Det: Foundation Model Guided Robust Object Detection0
CF-DETR: Coarse-to-Fine Transformer for Real-Time Object Detection0
Language-guided Learning for Object Detection Tackling Multiple Variations in Aerial Images0
WTEFNet: Real-Time Low-Light Object Detection for Advanced Driver-Assistance Systems0
The Meeseeks Mesh: Spatially Consistent 3D Adversarial Objects for BEV Detector0
VME: A Satellite Imagery Dataset and Benchmark for Detecting Vehicles in the Middle East and BeyondCode0
YH-MINER: Multimodal Intelligent System for Natural Ecological Reef Metric Extraction0
Task-Driven Implicit Representations for Automated Design of LiDAR Systems0
Roboflow100-VL: A Multi-Domain Object Detection Benchmark for Vision-Language ModelsCode2
A Novel Shape-Aware Topological Representation for GPR Data with DNN Integration0
ADD-SLAM: Adaptive Dynamic Dense SLAM with Gaussian Splatting0
Underwater Diffusion Attention Network with Contrastive Language-Image Joint Learning for Underwater Image Enhancement0
VL-SAM-V2: Open-World Object Detection with General and Specific Query Fusion0
Vision Meets Language: A RAG-Augmented YOLOv8 Framework for Coffee Disease Diagnosis and Farmer AssistanceCode0
Mitigating Context Bias in Domain Adaptation for Object Detection using Mask Pooling0
OrionBench: A Benchmark for Chart and Human-Recognizable Object Detection in InfographicsCode3
SemSegBench & DetecBench: Benchmarking Reliability and Generalization Beyond ClassificationCode0
RQR3D: Reparametrizing the regression targets for BEV-based 3D object detection0
Adaptive Semantic Token Communication for Transformer-based Edge InferenceCode1
Sampling Strategies for Efficient Training of Deep Learning Object Detection Algorithms0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Co-DETRbox mAP66Unverified
2InternImage-H (M3I Pre-training)box mAP65.5Unverified
3M3I Pre-training (InternImage-H)box mAP65.4Unverified
4MoCaEbox mAP65.1Unverified
5Co-DETR (Swin-L)box mAP64.8Unverified
6Focal-Stable-DINO (Focal-Huge, no TTA)box mAP64.8Unverified
7EVAbox mAP64.7Unverified
8Group DETR v2box mAP64.5Unverified
9FocalNet-H (DINO)box mAP64.4Unverified
10InternImage-XLbox mAP64.3Unverified