SOTAVerified

Object Detection

Papers

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Showing 5501–5550 of 10957 papers

TitleStatusHype
Quantized Feature Distillation for Network Quantization—0
Improving Online Lane Graph Extraction by Object-Lane Clustering—0
SMURF: Spatial Multi-Representation Fusion for 3D Object Detection with 4D Imaging Radar—0
Attacking by Aligning: Clean-Label Backdoor Attacks on Object DetectionCode0
MLF-DET: Multi-Level Fusion for Cross-Modal 3D Object Detection—0
Learned Scalable Video Coding For Humans and MachinesCode0
Knowledge Distillation for Object Detection: from generic to remote sensing datasets—0
Component-wise Power Estimation of Electrical Devices Using Thermal Imaging—0
A Quantum Convolutional Neural Network Approach for Object Detection and Classification—0
LiDAR-BEVMTN: Real-Time LiDAR Bird's-Eye View Multi-Task Perception Network for Autonomous Driving—0
Does Visual Pretraining Help End-to-End Reasoning?—0
Rethinking Intersection Over Union for Small Object Detection in Few-Shot Regime—0
ROFusion: Efficient Object Detection using Hybrid Point-wise Radar-Optical FusionCode0
Ada3D : Exploiting the Spatial Redundancy with Adaptive Inference for Efficient 3D Object Detection—0
Unified Open-Vocabulary Dense Visual Prediction—0
Multi-Task Cross-Modality Attention-Fusion for 2D Object Detection—0
Active Learning for Object Detection with Non-Redundant Informative Sampling—0
Monocular 3D Object Detection with LiDAR Guided Semi Supervised Active Learning—0
S2R-ViT for Multi-Agent Cooperative Perception: Bridging the Gap from Simulation to Reality—0
Analysing Gender Bias in Text-to-Image Models using Object DetectionCode0
KECOR: Kernel Coding Rate Maximization for Active 3D Object Detection—0
Deteksi Sampah di Permukaan dan Dalam Perairan pada Objek Video dengan Metode Robust and Efficient Post-Processing dan Tubelet-Level Bounding Box Linking—0
MPDIoU: A Loss for Efficient and Accurate Bounding Box Regression—0
Aeolus Ocean -- A simulation environment for the autonomous COLREG-compliant navigation of Unmanned Surface Vehicles using Deep Reinforcement Learning and Maritime Object DetectionCode0
Robotic surface exploration with vision and tactile sensing for cracks detection and characterisation—0
Multimodal Object Detection in Remote Sensing—0
YOLIC: An Efficient Method for Object Localization and Classification on Edge DevicesCode0
A New Dataset and Comparative Study for Aphid Cluster Detection—0
YOGA: Deep Object Detection in the Wild with Lightweight Feature Learning and Multiscale Attention—0
GVCCI: Lifelong Learning of Visual Grounding for Language-Guided Robotic ManipulationCode0
Flexible and Fully Quantized Ultra-Lightweight TinyissimoYOLO for Ultra-Low-Power Edge Systems—0
Bio-Inspired Night Image Enhancement Based on Contrast Enhancement and Denoising—0
Joint Salient Object Detection and Camouflaged Object Detection via Uncertainty-aware Learning—0
Q-YOLOP: Quantization-aware You Only Look Once for Panoptic Driving Perception—0
Preventing Errors in Person Detection: A Part-Based Self-Monitoring FrameworkCode0
Visible and infrared self-supervised fusion trained on a single example—0
HA-ViD: A Human Assembly Video Dataset for Comprehensive Assembly Knowledge UnderstandingCode0
Camouflaged Object Detection with Feature Grafting and Distractor AwareCode0
Artificial Eye for the Blind—0
Domain Generalized Object Detection for Remote Sensing ImagesCode0
Joint Perceptual Learning for Enhancement and Object Detection in Underwater Scenarios—0
Open-Vocabulary Object Detection via Scene Graph Discovery—0
PseudoCell: Hard Negative Mining as Pseudo Labeling for Deep Learning-Based Centroblast Cell DetectionCode0
RADiff: Controllable Diffusion Models for Radio Astronomical Maps Generation—0
Base Layer Efficiency in Scalable Human-Machine Coding—0
Object Recognition System on a Tactile Device for Visually Impaired—0
SVDM: Single-View Diffusion Model for Pseudo-Stereo 3D Object Detection—0
Line Graphics Digitization: A Step Towards Full AutomationCode0
Focusing on what to decode and what to train: SOV Decoding with Specific Target Guided DeNoising and Vision Language AdvisorCode0
Exploiting Richness of Learned Compressed Representation of Images for Semantic Segmentation—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