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 291–300 of 2042 papers

Title	Date	Tasks	Status	Hype
Exploring Novel Object Recognition and Spontaneous Location Recognition Machine Learning Analysis Techniques in Alzheimer's Mice	Dec 12, 2023	Object RecognitionPose Estimation	CodeCode Available	0
The Quest for an Integrated Set of Neural Mechanisms Underlying Object Recognition in Primates	Dec 10, 2023	ObjectObject Recognition	—Unverified	0
Scientific Preparation for CSST: Classification of Galaxy and Nebula/Star Cluster Based on Deep Learning	Dec 8, 2023	image-classificationImage Classification	—Unverified	0
Are Vision Transformers More Data Hungry Than Newborn Visual Systems?	Dec 5, 2023	ObjectObject Recognition	CodeCode Available	0
SRTransGAN: Image Super-Resolution using Transformer based Generative Adversarial Network	Dec 4, 2023	Binary ClassificationDecoder	—Unverified	0
COTR: Compact Occupancy TRansformer for Vision-based 3D Occupancy Prediction	Dec 4, 2023	3D geometryAutonomous Driving	CodeCode Available	1
Object Recognition as Next Token Prediction	Dec 4, 2023	DecoderLanguage Modeling	CodeCode Available	1
Foveation in the Era of Deep Learning	Dec 3, 2023	Deep LearningFoveation	CodeCode Available	0
Developmental Pretraining (DPT) for Image Classification Networks	Dec 1, 2023	Classificationimage-classification	CodeCode Available	0
Learning for Semantic Knowledge Base-Guided Online Feature Transmission in Dynamic Channels	Nov 30, 2023	Autonomous VehiclesDecision Making	—Unverified	0

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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