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 351–375 of 2042 papers

TitleStatusHype
Performance Assessment of Feature Detection Methods for 2-D FS Sonar Imagery—0
A Bayesian Framework for Active Tactile Object Recognition, Pose Estimation and Shape Transfer Learning—0
Fast Deep Predictive Coding Networks for Videos Feature Extraction without Labels—0
Limited but consistent gains in adversarial robustness by co-training object recognition models with human EEG—0
UAV (Unmanned Aerial Vehicles): Diverse Applications of UAV Datasets in Segmentation, Classification, Detection, and Tracking—0
Low-Resolution Object Recognition with Cross-Resolution Relational Contrastive Distillation—0
Discriminative Spatial-Semantic VOS Solution: 1st Place Solution for 6th LSVOSCode0
OpenNav: Efficient Open Vocabulary 3D Object Detection for Smart Wheelchair NavigationCode0
Optimizing Spatio-Temporal Information Processing in Spiking Neural Networks via Unconstrained Leaky Integrate-and-Fire Neurons and Hybrid CodingCode0
Finding Closure: A Closer Look at the Gestalt Law of Closure in Convolutional Neural Networks—0
How Small is Big Enough? Open Labeled Datasets and the Development of Deep Learning—0
Robust Domain Generalization for Multi-modal Object Recognition—0
ArtVLM: Attribute Recognition Through Vision-Based Prefix Language Modeling—0
Understanding How Blind Users Handle Object Recognition Errors: Strategies and Challenges—0
Source-Free Domain-Invariant Performance Prediction—0
A General Ambiguity Model for Binary Edge Images with Edge Tracing and its Implementation—0
THOR2: Topological Analysis for 3D Shape and Color-Based Human-Inspired Object Recognition in Unseen EnvironmentsCode0
EZSR: Event-based Zero-Shot Recognition—0
Combined CNN and ViT features off-the-shelf: Another astounding baseline for recognition—0
AI-based Density Recognition—0
A Dataset for Crucial Object Recognition in Blind and Low-Vision Individuals' NavigationCode0
Affordance Labeling and Exploration: A Manifold-Based Approach—0
EmoCAM: Toward Understanding What Drives CNN-based Emotion Recognition—0
OCTrack: Benchmarking the Open-Corpus Multi-Object Tracking—0
SUSTechGAN: Image Generation for Object Detection in Adverse Conditions of Autonomous DrivingCode0
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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