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 1651–1700 of 2042 papers

TitleStatusHype
Improved Deep Learning of Object Category using Pose Information—0
FusionNet: 3D Object Classification Using Multiple Data Representations—0
Training Skinny Deep Neural Networks with Iterative Hard Thresholding Methods—0
Distributed Coding of Multiview Sparse Sources with Joint Recovery—0
Do semantic parts emerge in Convolutional Neural Networks?—0
From Dependence to Causation—0
Deep Reconstruction-Classification Networks for Unsupervised Domain AdaptationCode0
Enlightening Deep Neural Networks with Knowledge of Confounding Factors—0
Captioning Images with Diverse ObjectsCode0
Saliency Driven Object recognition in egocentric videos with deep CNN—0
Mutual Exclusivity Loss for Semi-Supervised Deep Learning—0
Selective Unsupervised Feature Learning with Convolutional Neural Network (S-CNN)—0
View-tolerant face recognition and Hebbian learning imply mirror-symmetric neural tuning to head orientation—0
What is the Best Feature Learning Procedure in Hierarchical Recognition Architectures?—0
How Deep is the Feature Analysis underlying Rapid Visual Categorization?—0
On Recognizing Transparent Objects in Domestic Environments Using Fusion of Multiple Sensor Modalities—0
iLab-20M: A Large-Scale Controlled Object Dataset to Investigate Deep Learning—0
Approximate Log-Hilbert-Schmidt Distances Between Covariance Operators for Image Classification—0
Learning compact binary descriptors with unsupervised deep neural networksCode0
SPDA-CNN: Unifying Semantic Part Detection and Abstraction for Fine-Grained Recognition—0
Interactive Segmentation on RGBD Images via Cue Selection—0
Occlusion Boundary Detection via Deep Exploration of Context—0
BORDER: An Oriented Rectangles Approach to Texture-Less Object Recognition—0
Learning Compact Binary Descriptors With Unsupervised Deep Neural Networks—0
Modality and Component Aware Feature Fusion For RGB-D Scene Classification—0
Consistency of Silhouettes and Their Duals—0
Answer-Type Prediction for Visual Question Answering—0
Pairwise Linear Regression Classification for Image Set Retrieval—0
Predicting When Saliency Maps Are Accurate and Eye Fixations Consistent—0
Discriminative Multi-Modal Feature Fusion for RGBD Indoor Scene Recognition—0
Image Style Transfer Using Convolutional Neural NetworksCode0
Towards ontology driven learning of visual concept detectors—0
Applications of Probabilistic Programming (Master's thesis, 2015)—0
Generalized Multi-view Embedding for Visual Recognition and Cross-modal Retrieval—0
Latent Bi-constraint SVM for Video-based Object Recognition—0
Parametric Exponential Linear Unit for Deep Convolutional Neural Networks—0
Semi-supervised Zero-Shot Learning by a Clustering-based Approach—0
Pairwise Decomposition of Image Sequences for Active Multi-View Recognition—0
FPNN: Field Probing Neural Networks for 3D DataCode0
Hierarchical Piecewise-Constant Super-regions—0
Dual Local-Global Contextual Pathways for Recognition in Aerial Imagery—0
Incremental Robot Learning of New Objects with Fixed Update TimeCode0
Going Deeper into Action Recognition: A Survey—0
An Empirical Study and Analysis of Generalized Zero-Shot Learning for Object Recognition in the WildCode0
A New Manifold Distance Measure for Visual Object Categorization—0
ASP Vision: Optically Computing the First Layer of Convolutional Neural Networks using Angle Sensitive Pixels—0
Measurement Bounds for Sparse Signal Reconstruction with Multiple Side Information—0
A Theoretical Analysis of Deep Neural Networks for Texture Classification—0
Learning Attributes Equals Multi-Source Domain Generalization—0
1 Million Captioned Dutch Newspaper Images—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