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 1–50 of 2042 papers

TitleStatusHype
RTMDet: An Empirical Study of Designing Real-Time Object DetectorsCode4
Lightweight Pixel Difference Networks for Efficient Visual Representation LearningCode4
Detectron2 Object Detection & Manipulating Images using CartoonizationCode4
DALL-Eval: Probing the Reasoning Skills and Social Biases of Text-to-Image Generation ModelsCode3
UniBench: Visual Reasoning Requires Rethinking Vision-Language Beyond ScalingCode3
Interactive Medical Image Segmentation: A Benchmark Dataset and BaselineCode3
pix2gestalt: Amodal Segmentation by Synthesizing WholesCode3
Datasets: A Community Library for Natural Language ProcessingCode3
NUDT4MSTAR: A Large Dataset and Benchmark Towards Remote Sensing Object Recognition in the WildCode2
SceneGraphNet: Neural Message Passing for 3D Indoor Scene AugmentationCode2
InstructSAM: A Training-Free Framework for Instruction-Oriented Remote Sensing Object RecognitionCode2
Seeing the roads through the trees: A benchmark for modeling spatial dependencies with aerial imageryCode2
Taccel: Scaling Up Vision-based Tactile Robotics via High-performance GPU SimulationCode2
Lifting Multi-View Detection and Tracking to the Bird's Eye ViewCode2
Sparse R-CNN: End-to-End Object Detection with Learnable ProposalsCode2
A Simple Episodic Linear Probe Improves Visual Recognition in the WildCode2
Omni3D: A Large Benchmark and Model for 3D Object Detection in the WildCode2
Local Feature Matching Using Deep Learning: A SurveyCode2
Roboflow 100: A Rich, Multi-Domain Object Detection BenchmarkCode2
Some Improvements on Deep Convolutional Neural Network Based Image ClassificationCode2
StableSemantics: A Synthetic Language-Vision Dataset of Semantic Representations in Naturalistic ImagesCode2
Towards Language Models That Can See: Computer Vision Through the LENS of Natural LanguageCode2
P2Object: Single Point Supervised Object Detection and Instance SegmentationCode2
Is CLIP the main roadblock for fine-grained open-world perception?Code2
Hypergraph Neural NetworksCode2
A Simple Framework for Contrastive Learning of Visual RepresentationsCode2
Learning Transferable Visual Models From Natural Language SupervisionCode2
Patchwork++: Fast and Robust Ground Segmentation Solving Partial Under-Segmentation Using 3D Point CloudCode2
MG-LLaVA: Towards Multi-Granularity Visual Instruction TuningCode2
The Equalization Losses: Gradient-Driven Training for Long-tailed Object RecognitionCode2
GCNet: Non-local Networks Meet Squeeze-Excitation Networks and BeyondCode2
HAKE: A Knowledge Engine Foundation for Human Activity UnderstandingCode2
Discover and Cure: Concept-aware Mitigation of Spurious CorrelationCode1
Attribution in Scale and SpaceCode1
Distributed Deep Neural Networks over the Cloud, the Edge and End DevicesCode1
Describing Textures in the WildCode1
DetMatch: Two Teachers are Better Than One for Joint 2D and 3D Semi-Supervised Object DetectionCode1
Divergences in Color Perception between Deep Neural Networks and HumansCode1
Benchmarking Multimodal Mathematical Reasoning with Explicit Visual DependencyCode1
Densely Connected Convolutional NetworksCode1
DeepScores -- A Dataset for Segmentation, Detection and Classification of Tiny ObjectsCode1
Deep Predictive Coding Networks for Video Prediction and Unsupervised LearningCode1
Deep Subdomain Adaptation Network for Image ClassificationCode1
DesCo: Learning Object Recognition with Rich Language DescriptionsCode1
Do Adversarially Robust ImageNet Models Transfer Better?Code1
DaWin: Training-free Dynamic Weight Interpolation for Robust AdaptationCode1
Debiased Self-Training for Semi-Supervised LearningCode1
A Study of Face Obfuscation in ImageNetCode1
3D ShapeNets: A Deep Representation for Volumetric ShapesCode1
CSIM: A Copula-based similarity index sensitive to local changes for Image quality assessmentCode1
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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