SOTAVerified

Object Recognition

Object recognition is a computer vision technique for detecting + classifying objects in images or videos. Since this is a combined task of object detection plus image classification, the state-of-the-art tables are recorded for each component task here and here.

( Image credit: Tensorflow Object Detection API )

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 451–475 of 2042 papers

TitleStatusHype
Data-Driven 3D Voxel Patterns for Object Category Recognition—0
Data-driven Verification of DNNs for Object Recognition—0
Dataset for flood area recognition with semantic segmentation—0
Deep Transfer Learning: A new deep learning glitch classification method for advanced LIGO—0
DaTscan SPECT Image Classification for Parkinson's Disease—0
CNN-based search model underestimates attention guidance by simple visual features—0
DCENWCNet: A Deep CNN Ensemble Network for White Blood Cell Classification with LIME-Based Explainability—0
DCI: Discriminative and Contrast Invertible Descriptor—0
DCIRNet: Depth Completion with Iterative Refinement for Dexterous Grasping of Transparent and Reflective Objects—0
Application of Deep Learning in Generating Desired Design Options: Experiments Using Synthetic Training Dataset—0
Fractional order graph neural network—0
MIRAGE: A Multi-modal Benchmark for Spatial Perception, Reasoning, and Intelligence—0
A Feature Learning and Object Recognition Framework for Underwater Fish Images—0
ClusterNet: Deep Hierarchical Cluster Network With Rigorously Rotation-Invariant Representation for Point Cloud Analysis—0
Deep Affordance-grounded Sensorimotor Object Recognition—0
Deep Bayesian Image Set Classification: A Defence Approach against Adversarial Attacks—0
Deep Boosting of Diverse Experts—0
Deep Clustering by Semantic Contrastive Learning—0
Clustering Images by Unmasking - A New Baseline—0
A low-power end-to-end hybrid neuromorphic framework for surveillance applications—0
Application of 2D Homography for High Resolution Traffic Data Collection using CCTV Cameras—0
Deep Convolutional Neural Networks for Microscopy-Based Point of Care Diagnostics—0
Deep convolutional neural networks for brain image analysis on magnetic resonance imaging: a review—0
AU Dataset for Visuo-Haptic Object Recognition for Robots—0
3D Object Detection Method Based on YOLO and K-Means for Image and Point Clouds—0
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All datasetsshape biasCIFAR10-DVSN-Caltech 101ObjectNet (All classes)ObjectNet (ImageNet classes)ObjectNet (ImageNet classes, trained on ImageNet)DVS128 GestureMECCANON-CARS

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Imagenshape bias98.7—Unverified
2Stable Diffusionshape bias92.7—Unverified
3Partishape bias91.7—Unverified
4ViT-22B-384shape bias86.4—Unverified
5ViT-22B-560shape bias83.8—Unverified
6CLIP (ViT-B)shape bias79.9—Unverified
7ViT-22B-224shape bias78—Unverified
8ResNet-50 (L2 eps 5.0 adv trained)shape bias69.5—Unverified
9ResNet-50 (with strong augmentations)shape bias62.2—Unverified
10SWSL (ResNeXt-101)shape bias49.8—Unverified
#ModelMetricClaimedVerifiedStatus
1Spike-VGG11Accuracy (% )85.55—Unverified
2SSNNAccuracy (% )78.57—Unverified
#ModelMetricClaimedVerifiedStatus
1Spike-VGG11Accuracy (% )85.62—Unverified
2SSNNAccuracy (% )79.25—Unverified
#ModelMetricClaimedVerifiedStatus
1ObjectNet-BaselineTop 5 Accuracy18.75—Unverified
2yunTop 5 Accuracy14.75—Unverified
#ModelMetricClaimedVerifiedStatus
1ObjectNet-BaselineTop 5 Accuracy52.24—Unverified
2DYTop 5 Accuracy0.08—Unverified
#ModelMetricClaimedVerifiedStatus
1ObjectNet-BaselineTop 5 Accuracy52.24—Unverified
2AJ2021Top 5 Accuracy27.68—Unverified
#ModelMetricClaimedVerifiedStatus
1SSNNAccuracy (% )94.91—Unverified
#ModelMetricClaimedVerifiedStatus
1Faster-RCNNmAP30.39—Unverified
#ModelMetricClaimedVerifiedStatus
1Spike-VGG11Accuracy (% )96—Unverified