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 1076–1100 of 2042 papers

TitleStatusHype
Pixel-wise Segmentation of Street with Neural Networks—0
Place recognition survey: An update on deep learning approaches—0
PLAICraft: Large-Scale Time-Aligned Vision-Speech-Action Dataset for Embodied AI—0
Point Cloud Sampling via Graph Balancing and Gershgorin Disc Alignment—0
Pointing Novel Objects in Image Captioning—0
Polyhedral Object Recognition by Indexing—0
Poseidon: A System Architecture for Efficient GPU-based Deep Learning on Multiple Machines—0
Pose-Invariant Object Recognition for Event-Based Vision with Slow-ELM—0
Positive-Unlabeled Domain Adaptation—0
Pragmatic descriptions of perceptual stimuli—0
Predicting beauty, liking, and aesthetic quality: A comparative analysis of image databases for visual aesthetics research—0
Predicting the Road Ahead: A Knowledge Graph based Foundation Model for Scene Understanding in Autonomous Driving—0
Predicting When Saliency Maps Are Accurate and Eye Fixations Consistent—0
Pre-Trained Convolutional Neural Network Features for Facial Expression Recognition—0
Proactive Adversarial Defense: Harnessing Prompt Tuning in Vision-Language Models to Detect Unseen Backdoored Images—0
Importance Filtered Cross-Domain Adaptation—0
Procedural Text Generation from an Execution Video—0
Progressive Tandem Learning for Pattern Recognition with Deep Spiking Neural Networks—0
Projection: A Mechanism for Human-like Reasoning in Artificial Intelligence—0
PROTOTYPE-ASSISTED ADVERSARIAL LEARNING FOR UNSUPERVISED DOMAIN ADAPTATION—0
Prune and distill: similar reformatting of image information along rat visual cortex and deep neural networks—0
PseudoTouch: Efficiently Imaging the Surface Feel of Objects for Robotic Manipulation—0
Putting GPT-4o to the Sword: A Comprehensive Evaluation of Language, Vision, Speech, and Multimodal Proficiency—0
Quantifying Adversarial Sensitivity of a Model as a Function of the Image Distribution—0
Quantifying Translation-Invariance in Convolutional Neural Networks—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