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 401–450 of 2042 papers

TitleStatusHype
ContextLocNet: Context-Aware Deep Network Models for Weakly Supervised LocalizationCode0
ContextMix: A context-aware data augmentation method for industrial visual inspection systemsCode0
Causal importance of orientation selectivity for generalization in image recognitionCode0
Continual egocentric object recognitionCode0
FoodTracker: A Real-time Food Detection Mobile Application by Deep Convolutional Neural NetworksCode0
Fit to Measure: Reasoning about Sizes for Robust Object RecognitionCode0
A Comparative Analysis on Bangla Handwritten Digit Recognition with Data Augmentation and Non-Augmentation ProcessCode0
Food Image Recognition by Using Convolutional Neural Networks (CNNs)Code0
Continual Learning in Neural NetworksCode0
Continual Learning through Human-Robot Interaction: Human Perceptions of a Continual Learning Robot in Repeated InteractionsCode0
Image Style Transfer Using Convolutional Neural NetworksCode0
Multimodal Deep Learning for Robust RGB-D Object RecognitionCode0
Learning to Detect Important People in Unlabelled Images for Semi-supervised Important People DetectionCode0
Feature Learning for Accelerometer based Gait RecognitionCode0
Feature Learning by Multidimensional Scaling and its Applications in Object RecognitionCode0
Feature Pyramid GridsCode0
Cartesian K-MeansCode0
Faster gaze prediction with dense networks and Fisher pruningCode0
Fast Feature Fool: A data independent approach to universal adversarial perturbationsCode0
FewSOL: A Dataset for Few-Shot Object Learning in Robotic EnvironmentsCode0
Captioning Images with Diverse ObjectsCode0
Facial Expression Recognition Research Based on Deep LearningCode0
Exploring Novel Object Recognition and Spontaneous Location Recognition Machine Learning Analysis Techniques in Alzheimer's MiceCode0
Canonical Saliency Maps: Decoding Deep Face ModelsCode0
Finding Tiny FacesCode0
Object recognition in atmospheric turbulence scenesCode0
Can Large Language Models Grasp Event Signals? Exploring Pure Zero-Shot Event-based RecognitionCode0
Occlusion Coherence: Detecting and Localizing Occluded FacesCode0
Experiments with mmWave Automotive Radar Test-bedCode0
CORe50: a New Dataset and Benchmark for Continuous Object RecognitionCode0
EXOT: Exit-aware Object Tracker for Safe Robotic Manipulation of Moving ObjectCode0
BViT: Broad Attention based Vision TransformerCode0
3D_DEN: Open-ended 3D Object Recognition using Dynamically Expandable NetworksCode0
Fine-grained Attention and Feature-sharing Generative Adversarial Networks for Single Image Super-ResolutionCode0
Enhancing Pollinator Conservation towards Agriculture 4.0: Monitoring of Bees through Object RecognitionCode0
End-to-End Learning of Representations for Asynchronous Event-Based DataCode0
OpenLORIS-Object: A Robotic Vision Dataset and Benchmark for Lifelong Deep LearningCode0
OpenNav: Efficient Open Vocabulary 3D Object Detection for Smart Wheelchair NavigationCode0
Enabling My Robot To Play Pictionary : Recurrent Neural Networks For Sketch RecognitionCode0
Ensemble learning in CNN augmented with fully connected subnetworksCode0
Dynamic Rectification Knowledge DistillationCode0
EBPC: Extended Bit-Plane Compression for Deep Neural Network Inference and Training AcceleratorsCode0
A Classification approach towards Unsupervised Learning of Visual RepresentationsCode0
Breast Cancer Classification from Histopathological Images with Inception Recurrent Residual Convolutional Neural NetworkCode0
Efficient Event Stream Super-Resolution with Recursive Multi-Branch FusionCode0
DAAL: Density-Aware Adaptive Line Margin Loss for Multi-Modal Deep Metric LearningCode0
Don't Judge by the Look: Towards Motion Coherent Video RepresentationCode0
Training Deep Neural Networks via Branch-and-BoundCode0
Do Pre-trained Vision-Language Models Encode Object States?Code0
Domain Generalization via Model-Agnostic Learning of Semantic FeaturesCode0
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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