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

Showing 20012025 of 2042 papers

TitleStatusHype
Teaching CNNs to mimic Human Visual Cognitive Process & regularise Texture-Shape biasCode0
OrthographicNet: A Deep Transfer Learning Approach for 3D Object Recognition in Open-Ended DomainsCode0
Dynamic Rectification Knowledge DistillationCode0
A Survey on Bayesian Deep LearningCode0
Probing Human Visual Robustness with Neurally-Guided Deep Neural NetworksCode0
Do Pre-trained Vision-Language Models Encode Object States?Code0
Lifelong 3D Object Recognition and Grasp Synthesis Using Dual Memory Recurrent Self-Organization NetworksCode0
Robust Graph Learning from Noisy DataCode0
Lifelong Learning of Spatiotemporal Representations with Dual-Memory Recurrent Self-OrganizationCode0
Don't Judge by the Look: Towards Motion Coherent Video RepresentationCode0
Spatial Pyramid Pooling in Deep Convolutional Networks for Visual RecognitionCode0
Wiring Up Vision: Minimizing Supervised Synaptic Updates Needed to Produce a Primate Ventral StreamCode0
Robustness of Object Recognition under Extreme Occlusion in Humans and Computational ModelsCode0
DeepID3: Face Recognition with Very Deep Neural NetworksCode0
Dominant Set Clustering and Pooling for Multi-View 3D Object RecognitionCode0
Light Weight Residual Dense Attention Net for Spectral Reconstruction from RGB ImagesCode0
Domain Generalization via Model-Agnostic Learning of Semantic FeaturesCode0
Deep Feature Collaboration for Challenging 3D Finger Knuckle IdentificationCode0
Line-Circle-Square (LCS): A Multilayered Geometric Filter for Edge-Based DetectionCode0
The developmental trajectory of object recognition robustness: children are like small adults but unlike big deep neural networksCode0
Domain Generalization In Robust Invariant RepresentationCode0
Robust Sensible Adversarial Learning of Deep Neural Networks for Image ClassificationCode0
Local Aggregation for Unsupervised Learning of Visual EmbeddingsCode0
Domain Generalization by Solving Jigsaw PuzzlesCode0
Deep Discrete Hashing with Self-supervised Pairwise LabelsCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Imagenshape bias98.7Unverified
2Stable Diffusionshape bias92.7Unverified
3Partishape bias91.7Unverified
4ViT-22B-384shape bias86.4Unverified
5ViT-22B-560shape bias83.8Unverified
6CLIP (ViT-B)shape bias79.9Unverified
7ViT-22B-224shape bias78Unverified
8ResNet-50 (L2 eps 5.0 adv trained)shape bias69.5Unverified
9ResNet-50 (with strong augmentations)shape bias62.2Unverified
10SWSL (ResNeXt-101)shape bias49.8Unverified
#ModelMetricClaimedVerifiedStatus
1Spike-VGG11Accuracy (% )85.55Unverified
2SSNNAccuracy (% )78.57Unverified
#ModelMetricClaimedVerifiedStatus
1Spike-VGG11Accuracy (% )85.62Unverified
2SSNNAccuracy (% )79.25Unverified
#ModelMetricClaimedVerifiedStatus
1ObjectNet-BaselineTop 5 Accuracy18.75Unverified
2yunTop 5 Accuracy14.75Unverified
#ModelMetricClaimedVerifiedStatus
1ObjectNet-BaselineTop 5 Accuracy52.24Unverified
2DYTop 5 Accuracy0.08Unverified
#ModelMetricClaimedVerifiedStatus
1ObjectNet-BaselineTop 5 Accuracy52.24Unverified
2AJ2021Top 5 Accuracy27.68Unverified
#ModelMetricClaimedVerifiedStatus
1SSNNAccuracy (% )94.91Unverified
#ModelMetricClaimedVerifiedStatus
1Faster-RCNNmAP30.39Unverified
#ModelMetricClaimedVerifiedStatus
1Spike-VGG11Accuracy (% )96Unverified