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

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Showing 251–300 of 2042 papers

TitleStatusHype
Basic Level Categorization Facilitates Visual Object Recognition—0
An Adaptive Descriptor Design for Object Recognition in the Wild—0
Belief Tree Search for Active Object Recognition—0
Benchmarking Out-of-Distribution Generalization Capabilities of DNN-based Encoding Models for the Ventral Visual Cortex—0
A Machine Learning Framework for Distributed Functional Compression over Wireless Channels in IoT—0
A Bayesian Framework for Active Tactile Object Recognition, Pose Estimation and Shape Transfer Learning—0
Attribute-Based Classification for Zero-Shot Visual Object Categorization—0
A low-power end-to-end hybrid neuromorphic framework for surveillance applications—0
AttoNets: Compact and Efficient Deep Neural Networks for the Edge via Human-Machine Collaborative Design—0
Attention Mechanisms for Object Recognition with Event-Based Cameras—0
All-Weather Object Recognition Using Radar and Infrared Sensing—0
Adaptive Hierarchical Decomposition of Large Deep Networks—0
Cloud based Scalable Object Recognition from Video Streams using Orientation Fusion and Convolutional Neural Networks—0
Fractional order graph neural network—0
All About Knowledge Graphs for Actions—0
MIRAGE: A Multi-modal Benchmark for Spatial Perception, Reasoning, and Intelligence—0
A Transfer Learning Approach to Cross-Modal Object Recognition: From Visual Observation to Robotic Haptic Exploration—0
A Too-Good-to-be-True Prior to Reduce Shortcut Reliance—0
Aligning Text, Images, and 3D Structure Token-by-Token—0
A Theoretical Analysis of Deep Neural Networks for Texture Classification—0
A temporal neural network model for object recognition using a biologically plausible decision making layer—0
`Lighter' Can Still Be Dark: Modeling Comparative Color Descriptions—0
A Systematic Study on Object Recognition Using Millimeter-wave Radar—0
A Survey on Recent Advances of Computer Vision Algorithms for Egocentric Video—0
Adaptive Color Attributes for Real-Time Visual Tracking—0
AAD: Adaptive Anomaly Detection through traffic surveillance videos—0
CLIP-Nav: Using CLIP for Zero-Shot Vision-and-Language Navigation—0
CloudFort: Enhancing Robustness of 3D Point Cloud Classification Against Backdoor Attacks via Spatial Partitioning and Ensemble Prediction—0
Co-Attentive Equivariant Neural Networks: Focusing Equivariance On Transformations Co-Occurring In Data—0
A Survey of Task-Based Machine Learning Content Extraction Services for VIDINT—0
A Study of Image Pre-processing for Faster Object Recognition—0
Algorithms for Object Detection in Substations—0
A Study for Universal Adversarial Attacks on Texture Recognition—0
ALGO: Object-Grounded Visual Commonsense Reasoning for Open-World Egocentric Action Recognition—0
Adaptive Active Learning for Image Classification—0
Early or Late Fusion Matters: Efficient RGB-D Fusion in Vision Transformers for 3D Object Recognition—0
A large comparison of feature-based approaches for buried target classification in forward-looking ground-penetrating radar—0
A Label Correction Algorithm Using Prior Information for Automatic and Accurate Geospatial Object Recognition—0
Assessing The Importance Of Colours For CNNs In Object Recognition—0
ASP Vision: Optically Computing the First Layer of Convolutional Neural Networks using Angle Sensitive Pixels—0
A 51.3 TOPS/W, 134.4 GOPS In-memory Binary Image Filtering in 65nm CMOS—0
Classifying Malware Images with Convolutional Neural Network Models—0
A Spike Learning System for Event-driven Object Recognition—0
A spatiotemporal style transfer algorithm for dynamic visual stimulus generation—0
Airplane Type Identification Based on Mask RCNN; An Approach to Reduce Airport Traffic Congestion—0
A Simulation Method for MMW Radar Sensing in Traffic Intersection Based on BART Algorithm—0
AIris: An AI-powered Wearable Assistive Device for the Visually Impaired—0
Adaptation Across Extreme Variations using Unlabeled Domain Bridges—0
A ``Shape Aware'' Model for semi-supervised Learning of Objects and its Context—0
AI Recommendation System for Enhanced Customer Experience: A Novel Image-to-Text Method—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