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 501–550 of 2042 papers

TitleStatusHype
Object-Size-Driven Design of Convolutional Neural Networks: Virtual Axle Detection based on Raw Data—0
CoTDet: Affordance Knowledge Prompting for Task Driven Object Detection—0
Modeling infant object perception as program induction—0
Graph-based Asynchronous Event Processing for Rapid Object Recognition—0
Characterising representation dynamics in recurrent neural networks for object recognition—0
End-to-end topographic networks as models of cortical map formation and human visual behaviour: moving beyond convolutions—0
BSED: Baseline Shapley-Based Explainable Detector—0
Emergent communication for AR—0
Bootstrapping Developmental AIs: From Simple Competences to Intelligent Human-Compatible AIs—0
Surface Defects Detection of Transparent Plastic Bottles Based on Improved Yolov5—0
A semantics-driven methodology for high-quality image annotation—0
Does Progress On Object Recognition Benchmarks Improve Real-World Generalization?—0
Online Continual Learning for Robust Indoor Object Recognition—0
Human Action Recognition in Still Images Using ConViT—0
A Novel Explainable Artificial Intelligence Model in Image Classification problem—0
Self-supervised Optimization of Hand Pose Estimation using Anatomical Features and Iterative Learning—0
Object Recognition System on a Tactile Device for Visually Impaired—0
Predicting beauty, liking, and aesthetic quality: A comparative analysis of image databases for visual aesthetics research—0
Look, Remember and Reason: Grounded reasoning in videos with language models—0
Evaluation of Environmental Conditions on Object Detection using Oriented Bounding Boxes for AR Applications—0
Fine-grained 3D object recognition: an approach and experiments—0
Regulation of Mouse Learning and Mood by the Anti-Inflammatory Cytokine Interleukin-10—0
Object Detection based on the Collection of Geometric Evidence—0
Resume Information Extraction via Post-OCR Text Processing—0
Object Topological Character Acquisition by Inductive Learning—0
Sample-Efficient Learning of Novel Visual ConceptsCode0
Bayesian and Neural Inference on LSTM-based Object Recognition from Tactile and Kinesthetic InformationCode0
EXOT: Exit-aware Object Tracker for Safe Robotic Manipulation of Moving ObjectCode0
A newborn embodied Turing test for view-invariant object recognition—0
Performance-optimized deep neural networks are evolving into worse models of inferotemporal visual cortex—0
Adversarial alignment: Breaking the trade-off between the strength of an attack and its relevance to human perception—0
The ObjectFolder Benchmark: Multisensory Learning with Neural and Real Objects—0
CVSNet: A Computer Implementation for Central Visual System of The Brain—0
A Framework For Refining Text Classification and Object Recognition from Academic Articles—0
Are Deep Neural Networks Adequate Behavioural Models of Human Visual Perception?—0
Discovering Novel Actions from Open World Egocentric Videos with Object-Grounded Visual Commonsense Reasoning—0
Target-Aware Generative Augmentations for Single-Shot AdaptationCode0
Continual Learning through Human-Robot Interaction: Human Perceptions of a Continual Learning Robot in Repeated InteractionsCode0
CNN-based Methods for Object Recognition with High-Resolution Tactile SensorsCode0
How Deep Learning Sees the World: A Survey on Adversarial Attacks & Defenses—0
Effects of Real-Life Traffic Sign Alteration on YOLOv7- an Object Recognition Model—0
Egocentric Hierarchical Visual Semantics—0
GAANet: Ghost Auto Anchor Network for Detecting Varying Size Drones in DarkCode0
Persistent Homology Meets Object Unity: Object Recognition in ClutterCode0
HeteroEdge: Addressing Asymmetry in Heterogeneous Collaborative Autonomous Systems—0
Distributional Instance Segmentation: Modeling Uncertainty and High Confidence Predictions with Latent-MaskRCNN—0
A Systematic Study on Object Recognition Using Millimeter-wave Radar—0
Neurosymbolic AI - Why, What, and How—0
Deep Graph Reprogramming—0
Investigating the Nature of 3D Generalization in Deep Neural NetworksCode0
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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