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 201–250 of 2042 papers

TitleStatusHype
Doubly Right Object Recognition: A Why Prompt for Visual RationalesCode1
Dual-Hybrid Attention Network for Specular Highlight RemovalCode1
AdaNorm: Adaptive Gradient Norm Correction based Optimizer for CNNsCode1
E2PNet: Event to Point Cloud Registration with Spatio-Temporal Representation LearningCode1
Empirical Upper Bound, Error Diagnosis and Invariance Analysis of Modern Object DetectorsCode1
Egoshots, an ego-vision life-logging dataset and semantic fidelity metric to evaluate diversity in image captioning modelsCode1
Benchmarking Multimodal Mathematical Reasoning with Explicit Visual DependencyCode1
Enriching ImageNet with Human Similarity Judgments and Psychological EmbeddingsCode1
Equalization Loss for Long-Tailed Object RecognitionCode1
Improving ProtoNet for Few-Shot Video Object Recognition: Winner of ORBIT Challenge 2022Code1
Joint Distribution Matters: Deep Brownian Distance Covariance for Few-Shot ClassificationCode1
Lidar Annotation Is All You NeedCode1
EventRPG: Event Data Augmentation with Relevance Propagation GuidanceCode1
Evolving Deep Neural NetworksCode1
Adapting Self-Supervised Vision Transformers by Probing Attention-Conditioned Masking ConsistencyCode1
Explainability-Aware One Point Attack for Point Cloud Neural NetworksCode1
Exploit Clues from Views: Self-Supervised and Regularized Learning for Multiview Object RecognitionCode1
Explainable GeoAI: Can saliency maps help interpret artificial intelligence's learning process? An empirical study on natural feature detectionCode1
Exploring the Transferability of Visual Prompting for Multimodal Large Language ModelsCode1
A Study of Face Obfuscation in ImageNetCode1
Self-supervised learning of video representations from a child's perspectiveCode1
Human Pose Estimation for Real-World Crowded ScenariosCode0
A Dataset for Crucial Object Recognition in Blind and Low-Vision Individuals' NavigationCode0
A comparison between humans and AI at recognizing objects in unusual posesCode0
A Multi-viewpoint Outdoor Dataset for Human Action RecognitionCode0
How much human-like visual experience do current self-supervised learning algorithms need in order to achieve human-level object recognition?Code0
Human Eyes Inspired Recurrent Neural Networks are More Robust Against Adversarial NoisesCode0
Human-like Clustering with Deep Convolutional Neural NetworksCode0
HD-CNN: Hierarchical Deep Convolutional Neural Network for Large Scale Visual RecognitionCode0
Grounded Human-Object Interaction Hotspots from VideoCode0
Hidden in Plain Sight: Evaluating Abstract Shape Recognition in Vision-Language ModelsCode0
Grid-augmented vision: A simple yet effective approach for enhanced spatial understanding in multi-modal agentsCode0
Global Second-order Pooling Convolutional NetworksCode0
Grid Cell Path Integration For Movement-Based Visual Object RecognitionCode0
Hierarchical Superpixel Segmentation via Structural Information TheoryCode0
Tuned Compositional Feature Replays for Efficient Stream LearningCode0
Generalized Relevance Learning Grassmann QuantizationCode0
Ambient Sound Provides Supervision for Visual LearningCode0
Optimizing Spatio-Temporal Information Processing in Spiking Neural Networks via Unconstrained Leaky Integrate-and-Fire Neurons and Hybrid CodingCode0
Generate To Adapt: Aligning Domains using Generative Adversarial NetworksCode0
Generalisation in humans and deep neural networksCode0
Grasp Pre-shape Selection by Synthetic Training: Eye-in-hand Shared Control on the Hannes ProsthesisCode0
Genetic CNNCode0
FPNN: Field Probing Neural Networks for 3D DataCode0
Handwritten Bangla Character Recognition Using The State-of-Art Deep Convolutional Neural NetworksCode0
GAANet: Ghost Auto Anchor Network for Detecting Varying Size Drones in DarkCode0
Geometric and Textural Augmentation for Domain Gap ReductionCode0
Attention Based Pruning for Shift NetworksCode0
Improving Out-of-Distribution Detection with Disentangled Foreground and Background FeaturesCode0
On Adversarial Robustness of Point Cloud Semantic SegmentationCode0
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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