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 13011350 of 2042 papers

TitleStatusHype
Weighted Sigmoid Gate Unit for an Activation Function of Deep Neural Network0
Knowledge-guided Semantic Computing Network0
Deep learning systems as complex networks0
DEEP HIERARCHICAL MODEL FOR HIERARCHICAL SELECTIVE CLASSIFICATION AND ZERO SHOT LEARNING0
Semantic Topic Analysis of Traffic Camera Images0
Hypergraph Neural NetworksCode2
Semantic and structural image segmentation for prosthetic vision0
Learning to Localize and Align Fine-Grained Actions to Sparse Instructions0
Periocular Recognition Using CNN Features Off-the-Shelf0
Transparency and Explanation in Deep Reinforcement Learning Neural Networks0
Object-sensitive Deep Reinforcement Learning0
A Fog Robotic System for Dynamic Visual Servoing0
Non-iterative recomputation of dense layers for performance improvement of DCNN0
Context-Dependent Diffusion Network for Visual Relationship Detection0
A Variational Feature Encoding Method of 3D Object for Probabilistic Semantic SLAM0
AAD: Adaptive Anomaly Detection through traffic surveillance videos0
Generalisation in humans and deep neural networksCode0
PVNet: A Joint Convolutional Network of Point Cloud and Multi-View for 3D Shape RecognitionCode0
VERAM: View-Enhanced Recurrent Attention Model for 3D Shape Classification0
A Domain Guided CNN Architecture for Predicting Age from Structural Brain ImagesCode0
Parsing Geometry Using Structure-Aware Shape TemplatesCode0
Saliency for Fine-grained Object Recognition in Domains with Scarce Training Data0
Energy-based Tuning of Convolutional Neural Networks on Multi-GPUs0
Dynamic reshaping of functional brain networks during visual object recognition0
A recurrent multi-scale approach to RBG-D Object Recognition0
Active Object Perceiver: Recognition-guided Policy Learning for Object Searching on Mobile Robots0
Semantically Meaningful View SelectionCode0
Attention Mechanisms for Object Recognition with Event-Based Cameras0
Human peripheral blur is optimal for object recognition0
Big-Little Net: An Efficient Multi-Scale Feature Representation for Visual and Speech RecognitionCode0
PCL: Proposal Cluster Learning for Weakly Supervised Object DetectionCode1
End-to-End Race Driving with Deep Reinforcement Learning0
Kitting in the Wild through Online Domain Adaptation0
`Lighter' Can Still Be Dark: Modeling Comparative Color Descriptions0
Estimating Bicycle Route Attractivity from Image Data0
Syn2Real: A New Benchmark forSynthetic-to-Real Visual Domain Adaptation0
A temporal neural network model for object recognition using a biologically plausible decision making layer0
Physics-based Scene-level Reasoning for Object Pose Estimation in Clutter0
Task-Driven Convolutional Recurrent Models of the Visual SystemCode1
Deep Global-Connected Net With The Generalized Multi-Piecewise ReLU Activation in Deep Learning0
The Toybox Dataset of Egocentric Visual Object Transformations0
NetScore: Towards Universal Metrics for Large-scale Performance Analysis of Deep Neural Networks for Practical On-Device Edge Usage0
Convex Class Model on Symmetric Positive Definite Manifolds0
Delta-encoder: an effective sample synthesis method for few-shot object recognitionCode0
Model-based active learning to detect isometric deformable objects in the wild with deep architectures0
State Classification with CNN0
Recurrent Convolutional Fusion for RGB-D Object RecognitionCode0
Duplex Generative Adversarial Network for Unsupervised Domain Adaptation0
OLÉ: Orthogonal Low-Rank Embedding - A Plug and Play Geometric Loss for Deep LearningCode0
Geometry Aware Constrained Optimization Techniques for Deep Learning0
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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