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Object Detection

Papers

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Showing 3251–3275 of 10957 papers

TitleStatusHype
Accelerating Large Kernel Convolutions with Nested Winograd Transformation.pdf—0
Adversarial Attacks on Multi-task Visual Perception for Autonomous Driving—0
CNN-based Omnidirectional Object Detection for HermesBot Autonomous Delivery Robot with Preliminary Frame Classification—0
CNN based Multi-Instance Multi-Task Learning for Syndrome Differentiation of Diabetic Patients—0
A re-calibration method for object detection with multi-modal alignment bias in autonomous driving—0
CNN-Based Automatic Urinary Particles Recognition—0
Achieving Real-Time Object Detection on MobileDevices with Neural Pruning Search—0
3D Object Aided Self-Supervised Monocular Depth Estimation—0
Exploring Recurrent Long-term Temporal Fusion for Multi-view 3D Perception—0
CMR3D: Contextualized Multi-Stage Refinement for 3D Object Detection—0
CML-MOTS: Collaborative Multi-task Learning for Multi-Object Tracking and Segmentation—0
A Real-Time System for Egocentric Hand-Object Interaction Detection in Industrial Domains—0
Adversarial Attacks on Face Detectors using Neural Net based Constrained Optimization—0
A Real-Time Multi-Task Learning System for Joint Detection of Face, Facial Landmark and Head Pose—0
Achieving Real-Time LiDAR 3D Object Detection on a Mobile Device—0
Exploring Multi-Branch and High-Level Semantic Networks for Improving Pedestrian Detection—0
C-MIDN: Coupled Multiple Instance Detection Network With Segmentation Guidance for Weakly Supervised Object Detection—0
A real-time material breakage detection for offshore wind turbines based on improved neural network algorithm—0
CMDA: Cross-Modal and Domain Adversarial Adaptation for LiDAR-Based 3D Object Detection—0
CMAWRNet: Multiple Adverse Weather Removal via a Unified Quaternion Neural Architecture—0
Adversarial Attacks in a Multi-view Setting: An Empirical Study of the Adversarial Patches Inter-view Transferability—0
Exploring Multi-Modal Contextual Knowledge for Open-Vocabulary Object Detection—0
Cluttered Food Grasping with Adaptive Fingers and Synthetic-Data Trained Object Detection—0
A Real-time Junk Food Recognition System based on Machine Learning—0
ClusterNet: Detecting Small Objects in Large Scenes by Exploiting Spatio-Temporal Information—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