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

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Showing 1651–1700 of 2042 papers

TitleStatusHype
ASP Vision: Optically Computing the First Layer of Convolutional Neural Networks using Angle Sensitive Pixels—0
Assessing The Importance Of Colours For CNNs In Object Recognition—0
Early or Late Fusion Matters: Efficient RGB-D Fusion in Vision Transformers for 3D Object Recognition—0
A Study for Universal Adversarial Attacks on Texture Recognition—0
A Study of Image Pre-processing for Faster Object Recognition—0
A Survey of Task-Based Machine Learning Content Extraction Services for VIDINT—0
A Survey on Recent Advances of Computer Vision Algorithms for Egocentric Video—0
A Systematic Study on Object Recognition Using Millimeter-wave Radar—0
A temporal neural network model for object recognition using a biologically plausible decision making layer—0
A Theoretical Analysis of Deep Neural Networks for Texture Classification—0
A Too-Good-to-be-True Prior to Reduce Shortcut Reliance—0
A Transfer Learning Approach to Cross-Modal Object Recognition: From Visual Observation to Robotic Haptic Exploration—0
Attention Mechanisms for Object Recognition with Event-Based Cameras—0
AttoNets: Compact and Efficient Deep Neural Networks for the Edge via Human-Machine Collaborative Design—0
Attribute-Based Classification for Zero-Shot Visual Object Categorization—0
ATZSL: Defensive Zero-Shot Recognition in the Presence of Adversaries—0
AU Dataset for Visuo-Haptic Object Recognition for Robots—0
Audiovisual Highlight Detection in Videos—0
Auditing ImageNet: Towards a Model-driven Framework for Annotating Demographic Attributes of Large-Scale Image Datasets—0
Augmenting Image Annotation: A Human-LMM Collaborative Framework for Efficient Object Selection and Label Generation—0
Augmenting Strong Supervision Using Web Data for Fine-Grained Categorization—0
A Unifying Framework in Vector-valued Reproducing Kernel Hilbert Spaces for Manifold Regularization and Co-Regularized Multi-view Learning—0
Automatically Discovering Local Visual Material Attributes—0
Automatic Dataset Augmentation—0
Automatic Graphic Logo Detection via Fast Region-based Convolutional Networks—0
Automatic Ultrasound Image Segmentation of Supraclavicular Nerve Using Dilated U-Net Deep Learning Architecture—0
Autonomous Manipulation Learning for Similar Deformable Objects via Only One Demonstration—0
A Variational Feature Encoding Method of 3D Object for Probabilistic Semantic SLAM—0
Background Invariance Testing According to Semantic Proximity—0
Bandwidth limited object recognition in high resolution imagery—0
Basic Level Categorization Facilitates Visual Object Recognition—0
Belief Tree Search for Active Object Recognition—0
Benchmarking Out-of-Distribution Generalization Capabilities of DNN-based Encoding Models for the Ventral Visual Cortex—0
Benchmarking VLMs' Reasoning About Persuasive Atypical Images—0
Best Practices for Convolutional Neural Networks Applied to Object Recognition in Images—0
Better Exploiting OS-CNNs for Better Event Recognition in Images—0
Beyond Holistic Object Recognition: Enriching Image Understanding with Part States—0
Beyond Novelty Detection: Incongruent Events, when General and Specific Classifiers Disagree—0
Beyond Object Recognition: A New Benchmark towards Object Concept Learning—0
Beyond Recognition: Evaluating Visual Perspective Taking in Vision Language Models—0
Beyond Semantics: Rediscovering Spatial Awareness in Vision-Language Models—0
Beyond Sharing Weights for Deep Domain Adaptation—0
Beyond Spatial Pooling: Fine-Grained Representation Learning in Multiple Domains—0
Beyond Viewpoint: Robust 3D Object Recognition under Arbitrary Views through Joint Multi-Part Representation—0
GeoDE: a Geographically Diverse Evaluation Dataset for Object Recognition—0
BFO Meets HOG: Feature Extraction Based on Histograms of Oriented p.d.f. Gradients for Image Classification—0
big.LITTLE Vision Transformer for Efficient Visual Recognition—0
BIM-assisted object recognition for the on-site autonomous robotic assembly of discrete structures—0
BIM Hyperreality: Data Synthesis Using BIM and Hyperrealistic Rendering for Deep Learning—0
Binarized Neural Architecture Search for Efficient Object Recognition—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