SOTAVerified

Object Detection

Papers

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Showing 8401–8450 of 10957 papers

TitleStatusHype
Let's agree to disagree: learning highly debatable multirater labelling—0
Let's Roll: Synthetic Dataset Analysis for Pedestrian Detection Across Different Shutter Types—0
Let Synthetic Data Shine: Domain Reassembly and Soft-Fusion for Single Domain Generalization—0
Let There be Light: Improved Traffic Surveillance via Detail Preserving Night-to-Day Transfer—0
Level Set-Based Camera Pose Estimation From Multiple 2D/3D Ellipse-Ellipsoid Correspondences—0
Leverage Task Context for Object Affordance Ranking—0
Leveraging 3D LiDAR Sensors to Enable Enhanced Urban Safety and Public Health: Pedestrian Monitoring and Abnormal Activity Detection—0
Leveraging Captions in the Wild to Improve Object Detection—0
Leveraging Color Channel Independence for Improved Unsupervised Object Detection—0
Leveraging Confident Image Regions for Source-Free Domain-Adaptive Object Detection—0
Diminishing Domain Bias by Leveraging Domain Labels in Object Detection on UAVs—0
Leveraging Filter Correlations for Deep Model Compression—0
QSAM-Net: Rain streak removal by quaternion neural network with self-attention module—0
Leveraging Long-Range Temporal Relationships Between Proposals for Video Object Detection—0
Leveraging Multi-view Data for Improved Detection Performance: An Industrial Use Case—0
Leveraging object detection for the identification of lung cancer—0
Leveraging PointNet and PointNet++ for Lyft Point Cloud Classification Challenge—0
Leveraging Pre-Trained 3D Object Detection Models For Fast Ground Truth Generation—0
Leveraging Scene Geometry and Depth Information for Robust Image Deraining—0
Leveraging Self-Supervised Instance Contrastive Learning for Radar Object Detection—0
Leveraging Superfluous Information in Contrastive Representation Learning—0
QuadBEV: An Efficient Quadruple-Task Perception Framework via Bird's-Eye-View Representation—0
Leveraging Temporal Cues for Semi-Supervised Multi-View 3D Object Detection—0
Leveraging the Edge and Cloud for V2X-Based Real-Time Object Detection in Autonomous Driving—0
Break a Lag: Triple Exponential Moving Average for Enhanced Optimization—0
Leveraging Uncertainties for Deep Multi-modal Object Detection in Autonomous Driving—0
Accelerating Neural Network Inference by Overflow Aware Quantization—0
Multiple receptive fields and small-object-focusing weakly-supervised segmentation network for fast object detection—0
LGI-DETR: Local-Global Interaction for UAV Object Detection—0
Li3DeTr: A LiDAR based 3D Detection Transformer—0
LID 2020: The Learning from Imperfect Data Challenge Results—0
LiDAR-Aug: A General Rendering-Based Augmentation Framework for 3D Object Detection—0
LidarAugment: Searching for Scalable 3D LiDAR Data Augmentations—0
Lidar based Detection and Classification of Pedestrians and Vehicles Using Machine Learning Methods—0
Lidar-based Object Classification with Explicit Occlusion Modeling—0
QuAD: Query-based Interpretable Neural Motion Planning for Autonomous Driving—0
LiDAR-BEVMTN: Real-Time LiDAR Bird's-Eye View Multi-Task Perception Network for Autonomous Driving—0
LiDAR Cluster First and Camera Inference Later: A New Perspective Towards Autonomous Driving—0
1st Place Solutions for the UVO Challenge 2022—0
Quality-Aware Multimodal Saliency Detection via Deep Reinforcement Learning—0
LiDAR-guided object search and detection in Subterranean Environments—0
LiDAR-in-the-Loop Hyperparameter Optimization—0
Revisiting Cross-Domain Problem for LiDAR-based 3D Object Detection—0
LiDAR-MIMO: Efficient Uncertainty Estimation for LiDAR-based 3D Object Detection—0
LidarMultiNet: Towards a Unified Multi-Task Network for LiDAR Perception—0
LidarMultiNet: Unifying LiDAR Semantic Segmentation, 3D Object Detection, and Panoptic Segmentation in a Single Multi-task Network—0
LidarNAS: Unifying and Searching Neural Architectures for 3D Point Clouds—0
Quality Matters: Embracing Quality Clues for Robust 3D Multi-Object Tracking—0
Accelerating Federated Edge Learning via Topology Optimization—0
Accelerating Deep Neural Networks via Semi-Structured Activation Sparsity—0
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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