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 1851–1900 of 2042 papers

TitleStatusHype
Deep Learning from Parametrically Generated Virtual Buildings for Real-World Object Recognition—0
Deep Learning Object Detection Methods for Ecological Camera Trap Data—0
Deep learning systems as complex networks—0
Deep Learning Techniques for Geospatial Data Analysis—0
Deep Learning with Energy-efficient Binary Gradient Cameras—0
Deep Learning with Logged Bandit Feedback—0
DeepLogo: Hitting Logo Recognition with the Deep Neural Network Hammer—0
Deep Machine Learning Based Egyptian Vehicle License Plate Recognition Systems—0
Deep Mixture of Diverse Experts for Large-Scale Visual Recognition—0
Deep Models for Multi-View 3D Object Recognition: A Review—0
Deep Multi-View Learning using Neuron-Wise Correlation-Maximizing Regularizers—0
Deep Network Guided Proof Search—0
Deep Networks Can Resemble Human Feed-forward Vision in Invariant Object Recognition—0
Deep Neural Networks Can Learn Generalizable Same-Different Visual Relations—0
Deep Neural Networks predict Hierarchical Spatio-temporal Cortical Dynamics of Human Visual Object Recognition—0
Deep Neural Networks Rival the Representation of Primate IT Cortex for Core Visual Object Recognition—0
Deep Optical Coding Design in Computational Imaging—0
Deep Predictive Coding Network for Object Recognition—0
Deep Pyramidal Residual Networks with Separated Stochastic Depth—0
Deep RBFNet: Point Cloud Feature Learning using Radial Basis Functions—0
Deep Reinforcement Learning Models Predict Visual Responses in the Brain: A Preliminary Result—0
Deep Scene Image Classification With the MFAFVNet—0
DeepSIC: Deep Semantic Image Compression—0
Deep Sliding Shapes for Amodal 3D Object Detection in RGB-D Images—0
Deep Symmetry Networks—0
Deep Transfer Learning: A new deep learning glitch classification method for advanced LIGO—0
Deep Trans-layer Unsupervised Networks for Representation Learning—0
Deep Versus Wide Convolutional Neural Networks for Object Recognition on Neuromorphic System—0
Deep Watershed Detector for Music Object Recognition—0
Deflating Dataset Bias Using Synthetic Data Augmentation—0
Deformable Classifiers—0
Deformable Part Descriptors for Fine-grained Recognition and Attribute Prediction—0
Deformable Part Networks—0
Deformation-Invariant Neural Network and Its Applications in Distorted Image Restoration and Analysis—0
Deleting object selective units in a fully-connected layer of deep convolutional networks improves classification performance—0
Demonstration of 3D ISAR Security Imaging at 24GHz with a Sparse MIMO Array—0
Demystifying Contrastive Self-Supervised Learning: Invariances, Augmentations and Dataset Biases—0
Dense Semantic Correspondence where Every Pixel is a Classifier—0
Describing Images using Inferred Visual Dependency Representations—0
Describing Video Contents in Natural Language—0
Design Space Exploration of Hardware Spiking Neurons for Embedded Artificial Intelligence—0
Detailed Evaluation of Modern Machine Learning Approaches for Optic Plastics Sorting—0
Detecting and Correcting Adversarial Images Using Image Processing Operations—0
Detecting Deep Neural Network Defects with Data Flow Analysis—0
Detecting Visual Text—0
Detection Bank: An Object Detection Based Video Representation for Multimedia Event Recognition—0
Bootstrapping Developmental AIs: From Simple Competences to Intelligent Human-Compatible AIs—0
Development of an Inclusive Educational Platform Using Open Technologies and Machine Learning: A Case Study on Accessibility Enhancement—0
Development of collective behavior in newborn artificial agents—0
Development of Image Collection Method Using YOLO and Siamese Network—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