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 1501–1550 of 2042 papers

TitleStatusHype
Achieving Competitive Play Through Bottom-Up Approach in Semantic Segmentation—0
Achieving Domain Generalization in Underwater Object Detection by Domain Mixup and Contrastive Learning—0
Achieving Rotation Invariance in Convolution Operations: Shifting from Data-Driven to Mechanism-Assured—0
A Cognitive Approach based on the Actionable Knowledge Graph for supporting Maintenance Operations—0
A comparable study: Intrinsic difficulties of practical plant diagnosis from wide-angle images—0
A Comparative Survey of Vision Transformers for Feature Extraction in Texture Analysis—0
A Comparison of Few-Shot Learning Methods for Underwater Optical and Sonar Image Classification—0
A Comprehensive Review of Modern Object Segmentation Approaches—0
A Comprehensive Study of ImageNet Pre-Training for Historical Document Image Analysis—0
A concatenating framework of shortcut convolutional neural networks—0
A Convolutional Neural Network based Live Object Recognition System as Blind Aid—0
Active Gaze Behavior Boosts Self-Supervised Object Learning—0
Active Object Perceiver: Recognition-guided Policy Learning for Object Searching on Mobile Robots—0
Active Perception using Light Curtains for Autonomous Driving—0
Adaptation Across Extreme Variations using Unlabeled Domain Bridges—0
Adaptive Active Learning for Image Classification—0
Adaptive Color Attributes for Real-Time Visual Tracking—0
Fractional order graph neural network—0
Adaptive Hierarchical Decomposition of Large Deep Networks—0
Adaptive Object Detection with Dual Multi-Label Prediction—0
A DCNN-based Arbitrarily-Oriented Object Detector for Quality Control and Inspection Application—0
ADD-SLAM: Adaptive Dynamic Dense SLAM with Gaussian Splatting—0
A Deeper Look at the Unsupervised Learning of Disentangled Representations in β-VAE from the Perspective of Core Object Recognition—0
A Diffusion-based Data Generator for Training Object Recognition Models in Ultra-Range Distance—0
A Discriminative Representation of Convolutional Features for Indoor Scene Recognition—0
A Discriminative Vectorial Framework for Multi-modal Feature Representation—0
ADLDA: A Method to Reduce the Harm of Data Distribution Shift in Data Augmentation—0
A Dual-hierarchy Semantic Graph for Robust Object Recognition—0
Advancing Egocentric Video Question Answering with Multimodal Large Language Models—0
Adversarial alignment: Breaking the trade-off between the strength of an attack and its relevance to human perception—0
Adversarial Attack on Facial Recognition using Visible Light—0
Adversarial Attacks and Defense on Texts: A Survey—0
Adversarial Detection by Approximation of Ensemble Boundary—0
Adversarial Examples on Object Recognition: A Comprehensive Survey—0
Adversarial Examples on Segmentation Models Can be Easy to Transfer—0
Adversarial Fine-Grained Composition Learning for Unseen Attribute-Object Recognition—0
ADVISE: Symbolism and External Knowledge for Decoding Advertisements—0
A Dynamic Programming Approach for Fast and Robust Object Pose Recognition From Range Images—0
A dynamic vision sensor object recognition model based on trainable event-driven convolution and spiking attention mechanism—0
A Feature Learning and Object Recognition Framework for Underwater Fish Images—0
Affordance Labeling and Exploration: A Manifold-Based Approach—0
Afford-X: Generalizable and Slim Affordance Reasoning for Task-oriented Manipulation—0
A Fog Robotic System for Dynamic Visual Servoing—0
A Framework for Multi-View Classification of Features—0
A Framework For Refining Text Classification and Object Recognition from Academic Articles—0
A Generic Regression Framework for Pose Recognition on Color and Depth Images—0
Agricultural Object Detection with You Look Only Once (YOLO) Algorithm: A Bibliometric and Systematic Literature Review—0
A hierarchical framework for object recognition—0
A Hybrid APM-CPGSO Approach for Constraint Satisfaction Problem Solving: Application to Remote Sensing—0
AI-based Density Recognition—0
Show:102550
← PrevPage 31 of 41Next →
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