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 676–700 of 2042 papers

TitleStatusHype
Empowering Knowledge Distillation via Open Set Recognition for Robust 3D Point Cloud Classification—0
Empowering Local Communities Using Artificial Intelligence—0
Classifier-to-Generator Attack: Estimation of Training Data Distribution from Classifier—0
Enabling Pedestrian Safety using Computer Vision Techniques: A Case Study of the 2018 Uber Inc. Self-driving Car Crash—0
Encoder-Decoder based CNN and Fully Connected CRFs for Remote Sensed Image Segmentation—0
Encoding High Dimensional Local Features by Sparse Coding Based Fisher Vectors—0
End-to-End Auditory Object Recognition via Inception Nucleus—0
End-to-end Binary Representation Learning via Direct Binary Embedding—0
Class-specific Anchoring Proposal for 3D Object Recognition in LIDAR and RGB Images—0
Advancing Egocentric Video Question Answering with Multimodal Large Language Models—0
End-to-end topographic networks as models of cortical map formation and human visual behaviour: moving beyond convolutions—0
Energy-based Dropout in Restricted Boltzmann Machines: Why not go random—0
Energy-based Tuning of Convolutional Neural Networks on Multi-GPUs—0
Energy Efficient Hadamard Neural Networks—0
Enhanced Model Robustness to Input Corruptions by Per-corruption Adaptation of Normalization Statistics—0
Enhanced Multimodal RAG-LLM for Accurate Visual Question Answering—0
Enhancing 3D Object Detection in Autonomous Vehicles Based on Synthetic Virtual Environment Analysis—0
300 GHz Radar Object Recognition based on Deep Neural Networks and Transfer Learning—0
Enhancing efficiency of object recognition in different categorization levels by reinforcement learning in modular spiking neural networks—0
Enhancing Object Detection in Adverse Conditions using Thermal Imaging—0
Clustering Images by Unmasking - A New Baseline—0
Investigating the Role of Attribute Context in Vision-Language Models for Object Recognition and Detection—0
Enhancing Visual Representations for Efficient Object Recognition during Online Distillation—0
Enlightening Deep Neural Networks with Knowledge of Confounding Factors—0
Explaining Clinical Decision Support Systems in Medical Imaging using Cycle-Consistent Activation Maximization—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