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 18011850 of 2042 papers

TitleStatusHype
Multiscale Adaptive Representation of Signals: I. The Basic Framework0
Deep Learning and Music Adversaries0
Robot In a Room: Toward Perfect Object Recognition in Closed Environments0
Linking Entities Across Images and Text0
Describing Images using Inferred Visual Dependency Representations0
Occlusion Coherence: Detecting and Localizing Occluded FacesCode0
Natural Scene Recognition Based on Superpixels and Deep Boltzmann Machines0
A Novel Feature Extraction Method for Scene Recognition Based on Centered Convolutional Restricted Boltzmann Machines0
A Discriminative Representation of Convolutional Features for Indoor Scene Recognition0
Multi-path Convolutional Neural Networks for Complex Image ClassificationCode0
SVM and ELM: Who Wins? Object Recognition with Deep Convolutional Features from ImageNet0
Monocular SLAM Supported Object Recognition0
Exploiting an Oracle that Reports AUC Scores in Machine Learning Contests0
Is Object Localization for Free? - Weakly-Supervised Learning With Convolutional Neural Networks0
Recurrent Convolutional Neural Network for Object Recognition0
Beyond Spatial Pooling: Fine-Grained Representation Learning in Multiple Domains0
DeepContour: A Deep Convolutional Feature Learned by Positive-Sharing Loss for Contour Detection0
Semi-Supervised Domain Adaptation With Subspace Learning for Visual Recognition0
A Novel Locally Linear KNN Model for Visual Recognition0
Regularizing Max-Margin Exemplars by Reconstruction and Generative Models0
Data-Driven 3D Voxel Patterns for Object Category Recognition0
On the Relationship Between Visual Attributes and Convolutional Networks0
Zero-Shot Object Recognition by Semantic Manifold Distance0
Automatically Discovering Local Visual Material Attributes0
Understanding Tools: Task-Oriented Object Modeling, Learning and Recognition0
A Dynamic Programming Approach for Fast and Robust Object Pose Recognition From Range Images0
Hyper-Class Augmented and Regularized Deep Learning for Fine-Grained Image Classification0
CURL: Co-trained Unsupervised Representation Learning for Image Classification0
Texture Synthesis Using Convolutional Neural NetworksCode0
The Best of Both Worlds: Combining Data-independent and Data-driven Approaches for Action Recognition0
Robust Visual Knowledge Transfer via EDA0
Dense Semantic Correspondence where Every Pixel is a Classifier0
PISA: Pixelwise Image Saliency by Aggregating Complementary Appearance Contrast Measures with Edge-Preserving Coherence0
Sparse 3D convolutional neural networksCode0
Improving neural networks with bunches of neurons modeled by Kumaraswamy units: Preliminary study0
Learning to See by Moving0
ReNet: A Recurrent Neural Network Based Alternative to Convolutional NetworksCode0
Deep Learning and Continuous Representations for Natural Language Processing0
Exploit Bounding Box Annotations for Multi-label Object Recognition0
Bio-inspired Unsupervised Learning of Visual Features Leads to Robust Invariant Object Recognition0
Real-world Object Recognition with Off-the-shelf Deep Conv Nets: How Many Objects can iCub Learn?0
Real-time Monocular Object SLAM0
Kernel Manifold AlignmentCode0
A Probabilistic Theory of Deep LearningCode0
The Semantics of Image Annotation0
Generalized K-fan Multimodal Deep Model with Shared Representations0
Factorization of View-Object Manifolds for Joint Object Recognition and Pose Estimation0
Lifting Object Detection Datasets into 3D0
Do We Need More Training Data?0
Modelling Local Deep Convolutional Neural Network Features to Improve Fine-Grained Image Classification0
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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