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 811–820 of 2042 papers

Title	Date	Tasks	Status
Foveated Downsampling Techniques	Sep 11, 2019	FoveationObject Recognition	—Unverified
Continual Hyperbolic Learning of Instances and Classes	Jun 12, 2025	Continual LearningObject Recognition	—Unverified
Continual-Learning-as-a-Service (CLaaS): On-Demand Efficient Adaptation of Predictive Models	Jun 14, 2022	AttributeBIG-bench Machine Learning	—Unverified
iCub World: Friendly Robots Help Building Good Vision Data-Sets	Jun 15, 2013	Object Recognition	—Unverified
Context-Aware Zero-Shot Learning for Object Recognition	Apr 24, 2019	ObjectObject Recognition	—Unverified
Achieving Rotation Invariance in Convolution Operations: Shifting from Data-Driven to Mechanism-Assured	Apr 17, 2024	Data Augmentationimage-classification	—Unverified
From the Virtual to the RealWorld: Referring to Objects in Real-World Spatial Scenes	Sep 1, 2015	Object RecognitionText Generation	—Unverified
From Virtual to Real: A Framework for Verbal Interaction with Robots	Jun 1, 2019	Natural Language UnderstandingObject Recognition	—Unverified
From Visual Attributes to Adjectives through Decompositional Distributional Semantics	Jan 12, 2015	AttributeObject	—Unverified
Generating Clear Images From Images With Distortions Caused by Adverse Weather Using Generative Adversarial Networks	Nov 1, 2022	Autonomous DrivingAutonomous Vehicles	—Unverified

Show:10 25 50

← PrevPage 82 of 205Next →

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