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 451500 of 2042 papers

TitleStatusHype
Logical recognition method for solving the problem of identification in the Internet of Things0
A comparison between humans and AI at recognizing objects in unusual posesCode0
Motion Mapping Cognition: A Nondecomposable Primary Process in Human Vision0
EdgeOL: Efficient in-situ Online Learning on Edge Devices0
Achieving More Human Brain-Like Vision via Human EEG Representational Alignment0
EventF2S: Asynchronous and Sparse Spiking AER Framework using Neuromorphic-Friendly Algorithm0
The Machine Vision Iceberg Explained: Advancing Dynamic Testing by Considering Holistic Environmental Relations0
Synthetic data enables faster annotation and robust segmentation for multi-object grasping in clutter0
ContextMix: A context-aware data augmentation method for industrial visual inspection systemsCode0
Agricultural Object Detection with You Look Only Once (YOLO) Algorithm: A Bibliometric and Systematic Literature Review0
Geo-locating Road Objects using Inverse Haversine Formula with NVIDIA Driveworks0
Application of 2D Homography for High Resolution Traffic Data Collection using CCTV Cameras0
Meta-forests: Domain generalization on random forests with meta-learning0
Incorporating Geo-Diverse Knowledge into Prompting for Increased Geographical Robustness in Object Recognition0
Shrinking Your TimeStep: Towards Low-Latency Neuromorphic Object Recognition with Spiking Neural Network0
Layerwise complexity-matched learning yields an improved model of cortical area V20
Object Recognition from Scientific Document based on Compartment Refinement Framework0
Representational constraints underlying similarity between task-optimized neural systems0
Exploring Novel Object Recognition and Spontaneous Location Recognition Machine Learning Analysis Techniques in Alzheimer's MiceCode0
The Quest for an Integrated Set of Neural Mechanisms Underlying Object Recognition in Primates0
Scientific Preparation for CSST: Classification of Galaxy and Nebula/Star Cluster Based on Deep Learning0
Are Vision Transformers More Data Hungry Than Newborn Visual Systems?Code0
SRTransGAN: Image Super-Resolution using Transformer based Generative Adversarial Network0
Foveation in the Era of Deep LearningCode0
Developmental Pretraining (DPT) for Image Classification NetworksCode0
Learning for Semantic Knowledge Base-Guided Online Feature Transmission in Dynamic Channels0
Multi-3D-Models Registration-Based Augmented Reality (AR) Instructions for Assembly0
Polyhedral Object Recognition by Indexing0
DAS: A Deformable Attention to Capture Salient Information in CNNs0
AI Recommendation System for Enhanced Customer Experience: A Novel Image-to-Text Method0
Partial Coherence for Object Recognition and Depth Sensing0
Selective Visual Representations Improve Convergence and Generalization for Embodied AI0
Dataset for flood area recognition with semantic segmentation0
Open-Set Object Recognition Using Mechanical Properties During Interaction0
Deep Neural Networks Can Learn Generalizable Same-Different Visual Relations0
Does resistance to style-transfer equal Global Shape Bias? Measuring network sensitivity to global shape configurationCode0
V2X Cooperative Perception for Autonomous Driving: Recent Advances and Challenges0
Deformation-Invariant Neural Network and Its Applications in Distorted Image Restoration and Analysis0
How hard are computer vision datasets? Calibrating dataset difficulty to viewing time0
Recursive Counterfactual Deconfounding for Object Recognition0
Motion Segmentation from a Moving Monocular Camera0
Algorithms for Object Detection in Substations0
Edge Aware Learning for 3D Point Cloud0
Federated Learning in Intelligent Transportation Systems: Recent Applications and Open Problems0
Extreme Image Transformations Facilitate Robust Latent Object Representations0
Human-Inspired Topological Representations for Visual Object Recognition in Unseen Environments0
Hardening RGB-D Object Recognition Systems against Adversarial Patch Attacks0
RadarLCD: Learnable Radar-based Loop Closure Detection Pipeline0
Grounded Language Acquisition From Object and Action Imagery0
Reducing the False Positive Rate Using Bayesian Inference in Autonomous Driving Perception0
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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