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 51–100 of 2042 papers

TitleStatusHype
Comics Datasets Framework: Mix of Comics datasets for detection benchmarkingCode1
The 3D-PC: a benchmark for visual perspective taking in humans and machinesCode1
Bilateral Event Mining and Complementary for Event Stream Super-ResolutionCode1
Exploring the Transferability of Visual Prompting for Multimodal Large Language ModelsCode1
Two Effects, One Trigger: On the Modality Gap, Object Bias, and Information Imbalance in Contrastive Vision-Language ModelsCode1
EventRPG: Event Data Augmentation with Relevance Propagation GuidanceCode1
MiKASA: Multi-Key-Anchor & Scene-Aware Transformer for 3D Visual GroundingCode1
CLoVe: Encoding Compositional Language in Contrastive Vision-Language ModelsCode1
SHIELD : An Evaluation Benchmark for Face Spoofing and Forgery Detection with Multimodal Large Language ModelsCode1
Self-supervised learning of video representations from a child's perspectiveCode1
CLIP-guided Federated Learning on Heterogeneous and Long-Tailed DataCode1
COTR: Compact Occupancy TRansformer for Vision-based 3D Occupancy PredictionCode1
Object Recognition as Next Token PredictionCode1
E2PNet: Event to Point Cloud Registration with Spatio-Temporal Representation LearningCode1
Lidar Annotation Is All You NeedCode1
Recognize Any RegionsCode1
FSD: Fast Self-Supervised Single RGB-D to Categorical 3D ObjectsCode1
Matching the Neuronal Representations of V1 is Necessary to Improve Robustness in CNNs with V1-like Front-endsCode1
Intriguing properties of generative classifiersCode1
LMC: Large Model Collaboration with Cross-assessment for Training-Free Open-Set Object RecognitionCode1
Divergences in Color Perception between Deep Neural Networks and HumansCode1
Transformers in Small Object Detection: A Benchmark and Survey of State-of-the-ArtCode1
Large Separable Kernel Attention: Rethinking the Large Kernel Attention Design in CNNCode1
Decoding Natural Images from EEG for Object RecognitionCode1
Label-Free Event-based Object Recognition via Joint Learning with Image Reconstruction from EventsCode1
Scaling may be all you need for achieving human-level object recognition capacity with human-like visual experienceCode1
DesCo: Learning Object Recognition with Rich Language DescriptionsCode1
EventCLIP: Adapting CLIP for Event-based Object RecognitionCode1
Paxion: Patching Action Knowledge in Video-Language Foundation ModelsCode1
Learning Semi-supervised Gaussian Mixture Models for Generalized Category DiscoveryCode1
Discover and Cure: Concept-aware Mitigation of Spurious CorrelationCode1
From Chaos Comes Order: Ordering Event Representations for Object Recognition and DetectionCode1
Explainable GeoAI: Can saliency maps help interpret artificial intelligence's learning process? An empirical study on natural feature detectionCode1
Learning Efficient Coding of Natural Images with Maximum Manifold Capacity RepresentationsCode1
Deep Learning for Event-based Vision: A Comprehensive Survey and BenchmarksCode1
Towards Local Visual Modeling for Image CaptioningCode1
TempSAL -- Uncovering Temporal Information for Deep Saliency PredictionCode1
TempSAL - Uncovering Temporal Information for Deep Saliency PredictionCode1
Part-guided Relational Transformers for Fine-grained Visual RecognitionCode1
Doubly Right Object Recognition: A Why Prompt for Visual RationalesCode1
PASTA: Proportional Amplitude Spectrum Training Augmentation for Syn-to-Real Domain GeneralizationCode1
Learning Dense Object Descriptors from Multiple Views for Low-shot Category GeneralizationCode1
Harmonizing the object recognition strategies of deep neural networks with humansCode1
Object Segmentation of Cluttered Airborne LiDAR Point CloudsCode1
AdaNorm: Adaptive Gradient Norm Correction based Optimizer for CNNsCode1
Improving ProtoNet for Few-Shot Video Object Recognition: Winner of ORBIT Challenge 2022Code1
OBBStacking: An Ensemble Method for Remote Sensing Object DetectionCode1
BURST: A Benchmark for Unifying Object Recognition, Segmentation and Tracking in VideoCode1
Li-ion battery degradation modes diagnosis via Convolutional Neural NetworksCode1
Visual Recognition with Deep Nearest CentroidsCode1
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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