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 501–550 of 2042 papers

TitleStatusHype
Fast Feature Fool: A data independent approach to universal adversarial perturbationsCode0
Feature Learning for Accelerometer based Gait RecognitionCode0
Fine-grained Attention and Feature-sharing Generative Adversarial Networks for Single Image Super-ResolutionCode0
A Dataset for Crucial Object Recognition in Blind and Low-Vision Individuals' NavigationCode0
Bayesian and Neural Inference on LSTM-based Object Recognition from Tactile and Kinesthetic InformationCode0
Transformers: State-of-the-Art Natural Language ProcessingCode0
Triplet-Center Loss for Multi-View 3D Object RetrievalCode0
Foveation in the Era of Deep LearningCode0
Facial Expression Recognition Research Based on Deep LearningCode0
Exploring Novel Object Recognition and Spontaneous Location Recognition Machine Learning Analysis Techniques in Alzheimer's MiceCode0
EXOT: Exit-aware Object Tracker for Safe Robotic Manipulation of Moving ObjectCode0
An Analysis of Unsupervised Pre-training in Light of Recent AdvancesCode0
Experiments with mmWave Automotive Radar Test-bedCode0
Faster gaze prediction with dense networks and Fisher pruningCode0
FPNN: Field Probing Neural Networks for 3D DataCode0
Enhancing Pollinator Conservation towards Agriculture 4.0: Monitoring of Bees through Object RecognitionCode0
End-to-End Learning of Representations for Asynchronous Event-Based DataCode0
Ensemble learning in CNN augmented with fully connected subnetworksCode0
Deliberative Explanations: visualizing network insecuritiesCode0
EBPC: Extended Bit-Plane Compression for Deep Neural Network Inference and Training AcceleratorsCode0
Efficient Event Stream Super-Resolution with Recursive Multi-Branch FusionCode0
Enabling My Robot To Play Pictionary : Recurrent Neural Networks For Sketch RecognitionCode0
Do Pre-trained Vision-Language Models Encode Object States?Code0
Domain Generalization via Model-Agnostic Learning of Semantic FeaturesCode0
Don't Judge by the Look: Towards Motion Coherent Video RepresentationCode0
Domain Generalization by Solving Jigsaw PuzzlesCode0
Domain Generalization by Solving Jigsaw PuzzlesCode0
Does resistance to style-transfer equal Global Shape Bias? Measuring network sensitivity to global shape configurationCode0
Mixed Evidence for Gestalt Grouping in Deep Neural NetworksCode0
Domain-aware Triplet loss in Domain GeneralizationCode0
Domain Generalization In Robust Invariant RepresentationCode0
Dominant Set Clustering and Pooling for Multi-View 3D Object RecognitionCode0
Dynamic Rectification Knowledge DistillationCode0
Deep supervised learning for hyperspectral data classification through convolutional neural networksCode0
Diverse, Difficult, and Odd Instances (D2O): A New Test Set for Object ClassificationCode0
Disparity Sliding Window: Object Proposals From Disparity ImagesCode0
Distinctive Image Features from Scale-Invariant KeypointsCode0
DeepSat - A Learning framework for Satellite ImageryCode0
Delta-encoder: an effective sample synthesis method for few-shot object recognitionCode0
Big-Little Net: An Efficient Multi-Scale Feature Representation for Visual and Speech RecognitionCode0
Adding Knowledge to Unsupervised Algorithms for the Recognition of IntentCode0
Dense and Diverse Capsule Networks: Making the Capsules Learn BetterCode0
Discriminative Unsupervised Feature Learning with Convolutional Neural NetworksCode0
Task-generalizable Adversarial Attack based on Perceptual MetricCode0
Do deep nets really need weight decay and dropout?Code0
Deep Reconstruction-Classification Networks for Unsupervised Domain AdaptationCode0
Beyond accuracy: quantifying trial-by-trial behaviour of CNNs and humans by measuring error consistencyCode0
Temporal-Coded Deep Spiking Neural Network with Easy Training and Robust PerformanceCode0
Analysis and Optimization of Convolutional Neural Network ArchitecturesCode0
Deep Predictive Coding Network with Local Recurrent Processing for Object RecognitionCode0
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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