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 201–225 of 2042 papers

TitleStatusHype
ALGO: Object-Grounded Visual Commonsense Reasoning for Open-World Egocentric Action Recognition—0
Flexible ViG: Learning the Self-Saliency for Flexible Object Recognition—0
The 3D-PC: a benchmark for visual perspective taking in humans and machinesCode1
Haptic in-sensor computing device made of carbon nanotube-polydimethylsiloxane nanocomposites—0
A Review of Pulse-Coupled Neural Network Applications in Computer Vision and Image Processing—0
Face processing emerges from object-trained convolutional neural networks—0
MM-Mixing: Multi-Modal Mixing Alignment for 3D Understanding—0
Enhancing Pollinator Conservation towards Agriculture 4.0: Monitoring of Bees through Object RecognitionCode0
BiomedParse: a biomedical foundation model for image parsing of everything everywhere all at once—0
Transformer in Touch: A Survey—0
Zero-shot counting with a dual-stream neural network model—0
Bilateral Event Mining and Complementary for Event Stream Super-ResolutionCode1
AIris: An AI-powered Wearable Assistive Device for the Visually Impaired—0
ADLDA: A Method to Reduce the Harm of Data Distribution Shift in Data Augmentation—0
UnSegGNet: Unsupervised Image Segmentation using Graph Neural NetworksCode0
Probing Human Visual Robustness with Neurally-Guided Deep Neural NetworksCode0
SOAR: Advancements in Small Body Object Detection for Aerial Imagery Using State Space Models and Programmable Gradients—0
Imagine2touch: Predictive Tactile Sensing for Robotic Manipulation using Efficient Low-Dimensional SignalsCode0
Open-Set 3D Semantic Instance Maps for Vision Language Navigation -- O3D-SIMCode0
Deep Models for Multi-View 3D Object Recognition: A Review—0
CloudFort: Enhancing Robustness of 3D Point Cloud Classification Against Backdoor Attacks via Spatial Partitioning and Ensemble Prediction—0
On-board classification of underwater images using hybrid classical-quantum CNN based method—0
ECOR: Explainable CLIP for Object Recognition—0
How to deal with glare for improved perception of Autonomous Vehicles—0
Exploring the Transferability of Visual Prompting for Multimodal Large Language ModelsCode1
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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