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 601–625 of 2042 papers

TitleStatusHype
Automatic Graphic Logo Detection via Fast Region-based Convolutional Networks—0
Deep-learning-based classification and retrieval of components of a process plant from segmented point clouds—0
Deep Learning and Music Adversaries—0
Automatic Dataset Augmentation—0
A Multiclass Boosting Framework for Achieving Fast and Provable Adversarial Robustness—0
Deep Learning and Continuous Representations for Natural Language Processing—0
Automatically Discovering Local Visual Material Attributes—0
DEEP HIERARCHICAL MODEL FOR HIERARCHICAL SELECTIVE CLASSIFICATION AND ZERO SHOT LEARNING—0
A Unifying Framework in Vector-valued Reproducing Kernel Hilbert Spaces for Manifold Regularization and Co-Regularized Multi-view Learning—0
Amplitude-Based Approach to Evidence Accumulation—0
Deep Graph Reprogramming—0
Deep Global-Connected Net With The Generalized Multi-Piecewise ReLU Activation in Deep Learning—0
Augmenting Strong Supervision Using Web Data for Fine-Grained Categorization—0
DeepGaze II: Reading fixations from deep features trained on object recognition—0
Augmenting Image Annotation: A Human-LMM Collaborative Framework for Efficient Object Selection and Label Generation—0
Amodal Completion and Size Constancy in Natural Scenes—0
A Benchmark Grocery Dataset of Realworld Point Clouds From Single View—0
A Light and Smart Wearable Platform with Multimodal Foundation Model for Enhanced Spatial Reasoning in People with Blindness and Low Vision—0
Auditing ImageNet: Towards a Model-driven Framework for Annotating Demographic Attributes of Large-Scale Image Datasets—0
Audiovisual Highlight Detection in Videos—0
Deep convolutional neural networks for brain image analysis on magnetic resonance imaging: a review—0
AU Dataset for Visuo-Haptic Object Recognition for Robots—0
Deep Convolutional Neural Networks for Microscopy-Based Point of Care Diagnostics—0
DeepContour: A Deep Convolutional Feature Learned by Positive-Sharing Loss for Contour Detection—0
ATZSL: Defensive Zero-Shot Recognition in the Presence of Adversaries—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