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 Added Most Hyped Most Active Needs Verification Most Verified

Showing 31–40 of 2042 papers

Title	Date	Tasks	Status	Hype
Hypergraph Neural Networks	Sep 25, 2018	Object RecognitionRepresentation Learning	CodeCode Available	2
Some Improvements on Deep Convolutional Neural Network Based Image Classification	Dec 19, 2013	ClassificationGeneral Classification	CodeCode Available	2
STSBench: A Spatio-temporal Scenario Benchmark for Multi-modal Large Language Models in Autonomous Driving	Jun 6, 2025	Autonomous DrivingAutonomous Vehicles	CodeCode Available	1
Benchmarking Multimodal Mathematical Reasoning with Explicit Visual Dependency	Apr 24, 2025	BenchmarkingMath	CodeCode Available	1
Spatial457: A Diagnostic Benchmark for 6D Spatial Reasoning of Large Multimodal Models	Feb 12, 2025	AttributeDiagnostic	CodeCode Available	1
Comprehensive Multi-Modal Prototypes are Simple and Effective Classifiers for Vast-Vocabulary Object Detection	Dec 23, 2024	object-detectionObject Detection	CodeCode Available	1
CREST: An Efficient Conjointly-trained Spike-driven Framework for Event-based Object Detection Exploiting Spatiotemporal Dynamics	Dec 17, 2024	Objectobject-detection	CodeCode Available	1
WiseAD: Knowledge Augmented End-to-End Autonomous Driving with Vision-Language Model	Dec 13, 2024	Autonomous DrivingDecision Making	CodeCode Available	1
Expanding Event Modality Applications through a Robust CLIP-Based Encoder	Dec 4, 2024	Few-Shot LearningObject Recognition	CodeCode Available	1
LRSAA: Large-scale Remote Sensing Image Target Recognition and Automatic Annotation	Nov 24, 2024	Ensemble LearningObject	CodeCode Available	1

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All datasets shape bias CIFAR10-DVS N-Caltech 101 ObjectNet (All classes)ObjectNet (ImageNet classes)ObjectNet (ImageNet classes, trained on ImageNet)DVS128 Gesture MECCANO N-CARS

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	Imagen	shape bias	98.7	—	Unverified
2	Stable Diffusion	shape bias	92.7	—	Unverified
3	Parti	shape bias	91.7	—	Unverified
4	ViT-22B-384	shape bias	86.4	—	Unverified
5	ViT-22B-560	shape bias	83.8	—	Unverified
6	CLIP (ViT-B)	shape bias	79.9	—	Unverified
7	ViT-22B-224	shape bias	78	—	Unverified
8	ResNet-50 (L2 eps 5.0 adv trained)	shape bias	69.5	—	Unverified
9	ResNet-50 (with strong augmentations)	shape bias	62.2	—	Unverified
10	SWSL (ResNeXt-101)	shape bias	49.8	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Spike-VGG11	Accuracy (% )	85.55	—	Unverified
2	SSNN	Accuracy (% )	78.57	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Spike-VGG11	Accuracy (% )	85.62	—	Unverified
2	SSNN	Accuracy (% )	79.25	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	ObjectNet-Baseline	Top 5 Accuracy	18.75	—	Unverified
2	yun	Top 5 Accuracy	14.75	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	ObjectNet-Baseline	Top 5 Accuracy	52.24	—	Unverified
2	DY	Top 5 Accuracy	0.08	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	ObjectNet-Baseline	Top 5 Accuracy	52.24	—	Unverified
2	AJ2021	Top 5 Accuracy	27.68	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	SSNN	Accuracy (% )	94.91	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Faster-RCNN	mAP	30.39	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Spike-VGG11	Accuracy (% )	96	—	Unverified