SOTAVerified

Object Detection

Papers

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Showing 10351–10400 of 10957 papers

TitleStatusHype
SQuantizer: Simultaneous Learning for Both Sparse and Low-precision Neural Networks—0
Square Localization for Efficient and Accurate Object Detection—0
Squeezed Edge YOLO: Onboard Object Detection on Edge Devices—0
SqueezeJet: High-level Synthesis Accelerator Design for Deep Convolutional Neural Networks—0
SqueezeSAM: User friendly mobile interactive segmentation—0
SRCD: Semantic Reasoning with Compound Domains for Single-Domain Generalized Object Detection—0
SS3D: Single Shot 3D Object Detector—0
SS3D: Sparsely-Supervised 3D Object Detection From Point Cloud—0
SSAL: Synergizing between Self-Training and Adversarial Learning for Domain Adaptive Object Detection—0
SSBNet: Improving Visual Recognition Efficiency by Adaptive Sampling—0
SSC3OD: Sparsely Supervised Collaborative 3D Object Detection from LiDAR Point Clouds—0
SSF3D: Strict Semi-Supervised 3D Object Detection with Switching Filter—0
SSF-PAN: Semantic Scene Flow-Based Perception for Autonomous Navigation in Traffic Scenarios—0
SSGA-Net: Stepwise Spatial Global-local Aggregation Networks for for Autonomous Driving—0
SSL-OTA: Unveiling Backdoor Threats in Self-Supervised Learning for Object Detection—0
SSMD: Semi-Supervised Medical Image Detection with Adaptive Consistency and Heterogeneous Perturbation—0
SSMI: How to Make Objects of Interest Disappear without Accessing Object Detectors?—0
SSNet: Saliency Prior and State Space Model-based Network for Salient Object Detection in RGB-D Images—0
SS-SFR: Synthetic Scenes Spatial Frequency Response on Virtual KITTI and Degraded Automotive Simulations for Object Detection—0
SSTN: Self-Supervised Domain Adaptation Thermal Object Detection for Autonomous Driving—0
ST3D++: Denoised Self-training for Unsupervised Domain Adaptation on 3D Object Detection—0
Stability Plasticity Decoupled Fine-tuning For Few-shot end-to-end Object Detection—0
Stable Diffusion For Aerial Object Detection—0
Stable Diffusion for Data Augmentation in COCO and Weed Datasets—0
Stacking With Auxiliary Features—0
Staircase Localization for Autonomous Exploration in Urban Environments—0
STAL3D: Unsupervised Domain Adaptation for 3D Object Detection via Collaborating Self-Training and Adversarial Learning—0
StandardSim: A Synthetic Dataset For Retail Environments—0
StarNet: Targeted Computation for Object Detection in Point Clouds—0
State of the art applications of deep learning within tracking and detecting marine debris: A survey—0
State-of-the-art Models for Object Detection in Various Fields of Application—0
Static-Dynamic Co-Teaching for Class-Incremental 3D Object Detection—0
Static object detection and segmentation in videos based on dual foregrounds difference with noise filtering—0
Stating the Obvious: Extracting Visual Common Sense Knowledge—0
STAU: A SpatioTemporal-Aware Unit for Video Prediction and Beyond—0
STDepthFormer: Predicting Spatio-temporal Depth from Video with a Self-supervised Transformer Model—0
ST-DETR: Spatio-Temporal Object Traces Attention Detection Transformer—0
STD: Sparse-to-Dense 3D Object Detector for Point Cloud—0
Steal Now and Attack Later: Evaluating Robustness of Object Detection against Black-box Adversarial Attacks—0
STEAM: Squeeze and Transform Enhanced Attention Module—0
Steerable Equivariant Representation Learning—0
Stereo CenterNet based 3D Object Detection for Autonomous Driving—0
StereoDistill: Pick the Cream from LiDAR for Distilling Stereo-based 3D Object Detection—0
Stereo Frustums: A Siamese Pipeline for 3D Object Detection—0
Stereo RGB and Deeper LIDAR Based Network for 3D Object Detection—0
Stereo Superpixel Segmentation Via Decoupled Dynamic Spatial-Embedding Fusion Network—0
Stereo Vision for Unmanned Aerial VehicleDetection, Tracking, and Motion Control—0
STFAR: Improving Object Detection Robustness at Test-Time by Self-Training with Feature Alignment Regularization—0
STINet: Spatio-Temporal-Interactive Network for Pedestrian Detection and Trajectory Prediction—0
Stingray Detection of Aerial Images Using Augmented Training Images Generated by A Conditional Generative Model—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