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 526–550 of 2042 papers

TitleStatusHype
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