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 1026–1050 of 2042 papers

TitleStatusHype
Human-like general language processing—0
Visual Relationship Detection using Scene Graphs: A Survey—0
Ventral-Dorsal Neural Networks: Object Detection via Selective Attention—0
A Comparison of Few-Shot Learning Methods for Underwater Optical and Sonar Image Classification—0
How Can CNNs Use Image Position for Segmentation?—0
Illumination-Invariant Image from 4-Channel Images: The Effect of Near-Infrared Data in Shadow Removal—0
Immersive Language Exploration with Object Recognition and Augmented Reality—0
Deflating Dataset Bias Using Synthetic Data Augmentation—0
IROS 2019 Lifelong Robotic Vision Challenge -- Lifelong Object Recognition Report—0
A Deeper Look at the Unsupervised Learning of Disentangled Representations in β-VAE from the Perspective of Core Object Recognition—0
YCB-M: A Multi-Camera RGB-D Dataset for Object Recognition and 6DoF Pose Estimation—0
Unsupervised Domain Adaptation through Inter-modal Rotation for RGB-D Object RecognitionCode0
3D Object Detection Method Based on YOLO and K-Means for Image and Point Clouds—0
YOLO and K-Means Based 3D Object Detection Method on Image and Point Cloud—0
Five Points to Check when Comparing Visual Perception in Humans and MachinesCode0
Scaling the training of particle classification on simulated MicroBooNE events to multiple GPUs—0
Learning to Detect Important People in Unlabelled Images for Semi-supervised Important People DetectionCode0
CAggNet: Crossing Aggregation Network for Medical Image Segmentation—0
Light Weight Residual Dense Attention Net for Spectral Reconstruction from RGB ImagesCode0
MotionRec: A Unified Deep Framework for Moving Object Recognition—0
Feature Pyramid GridsCode0
Randomized Kernel Multi-view Discriminant Analysis—0
Semantic Domain Adversarial Networks for Unsupervised Domain Adaptation—0
Adaptive Object Detection with Dual Multi-Label Prediction—0
Classification of COVID-19 in chest X-ray images using DeTraC deep convolutional neural networkCode0
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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