SOTAVerified

Object Detection

Papers

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Showing 4051–4100 of 10957 papers

TitleStatusHype
Exploring Recurrent Long-term Temporal Fusion for Multi-view 3D Perception—0
LEDetection: A Simple Framework for Semi-Supervised Few-Shot Object DetectionCode1
Bi3D: Bi-domain Active Learning for Cross-domain 3D Object Detection—0
Automatic Detection and Rectification of Paper Receipts on Smartphones—0
Rethinking Self-Supervised Visual Representation Learning in Pre-training for 3D Human Pose and Shape Estimation—0
ARS-DETR: Aspect Ratio-Sensitive Detection Transformer for Aerial Oriented Object DetectionCode1
Tucker Bilinear Attention Network for Multi-scale Remote Sensing Object DetectionCode0
Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object DetectionCode5
Efficient Transformer-based 3D Object Detection with Dynamic Token Halting—0
NIFF: Alleviating Forgetting in Generalized Few-Shot Object Detection via Neural Instance Feature Forging—0
Smooth and Stepwise Self-Distillation for Object Detection—0
DDS3D: Dense Pseudo-Labels with Dynamic Threshold for Semi-Supervised 3D Object DetectionCode1
Weakly Supervised Knowledge Transfer with Probabilistic Logical Reasoning for Object DetectionCode0
You Only Crash Once: Improved Object Detection for Real-Time, Sim-to-Real Hazardous Terrain Detection and Classification for Autonomous Planetary Landings—0
Full Point Encoding for Local Feature Aggregation in 3D Point Clouds—0
HyT-NAS: Hybrid Transformers Neural Architecture Search for Edge Devices—0
Radio astronomical images object detection and segmentation: A benchmark on deep learning methods—0
FFT-based Dynamic Token Mixer for VisionCode1
LoGoNet: Towards Accurate 3D Object Detection with Local-to-Global Cross-Modal FusionCode0
Calibration-free BEV Representation for Infrastructure PerceptionCode1
Patch of Invisibility: Naturalistic Physical Black-Box Adversarial Attacks on Object DetectorsCode0
Gradient-Guided Knowledge Distillation for Object Detectors—0
Refined Pseudo labeling for Source-free Domain Adaptive Object Detection—0
FIT: Frequency-based Image Translation for Domain Adaptive Object Detection—0
Memory Maps for Video Object Detection and Tracking on UAVs—0
Can an Embodied Agent Find Your "Cat-shaped Mug"? LLM-Guided Exploration for Zero-Shot Object NavigationCode1
Pseudo-label Correction and Learning For Semi-Supervised Object Detection—0
EvCenterNet: Uncertainty Estimation for Object Detection using Evidential Learning—0
Boundary-semantic collaborative guidance network with dual-stream feedback mechanism for salient object detection in optical remote sensing imageryCode0
UniHCP: A Unified Model for Human-Centric PerceptionsCode1
Automatic detection of aerial survey ground control points based on Yolov5-OBB—0
A System for Generalized 3D Multi-Object SearchCode1
Scalable Object Detection on Embedded Devices Using Weight Pruning and Singular Value Decomposition—0
CueCAn: Cue Driven Contextual Attention For Identifying Missing Traffic Signs on Unconstrained Roads—0
Virtual Sparse Convolution for Multimodal 3D Object DetectionCode2
Real-time SLAM Pipeline in Dynamics Environment—0
R-TOSS: A Framework for Real-Time Object Detection using Semi-Structured Pruning—0
AdvART: Adversarial Art for Camouflaged Object Detection Attacks—0
Quantifying the LiDAR Sim-to-Real Domain Shift: A Detailed Investigation Using Object Detectors and Analyzing Point Clouds at Target-LevelCode0
Visual Exemplar Driven Task-Prompting for Unified Perception in Autonomous Driving—0
BSH-Det3D: Improving 3D Object Detection with BEV Shape HeatmapCode1
Towards Domain Generalization for Multi-view 3D Object Detection in Bird-Eye-View—0
X^3KD: Knowledge Distillation Across Modalities, Tasks and Stages for Multi-Camera 3D Object Detection—0
Visual Perception System for Autonomous Driving—0
Robust Detection Outcome: A Metric for Pathology Detection in Medical ImagesCode1
Confidence-driven Bounding Box Localization for Small Object Detection—0
A Coarse to Fine Framework for Object Detection in High Resolution Image—0
FeatAug-DETR: Enriching One-to-Many Matching for DETRs with Feature AugmentationCode1
Do Machine Learning Models Learn Statistical Rules Inferred from Data?Code0
Using simulation to quantify the performance of automotive perception systems—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