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 1971–1980 of 2042 papers

Title	Date	Tasks	Status
EIT-1M: One Million EEG-Image-Text Pairs for Human Visual-textual Recognition and More	Jul 2, 2024	EEGObject Recognition	—Unverified
Embedding Visual Hierarchy with Deep Networks for Large-Scale Visual Recognition	Jul 8, 2017	ObjectObject Recognition	—Unverified
EmBench: Quantifying Performance Variations of Deep Neural Networks across Modern Commodity Devices	May 17, 2019	Object Recognition	—Unverified
Embodied vision for learning object representations	May 12, 2022	Contrastive LearningObject	—Unverified
Emergent communication for AR	Aug 12, 2023	Cloud ComputingObject Recognition	—Unverified
EmoCAM: Toward Understanding What Drives CNN-based Emotion Recognition	Jul 19, 2024	Emotion Recognitionimage-classification	—Unverified
EMPIRICAL UPPER BOUND IN OBJECT DETECTION	Jan 1, 2021	Instance SegmentationObject	—Unverified
Empowering Knowledge Distillation via Open Set Recognition for Robust 3D Point Cloud Classification	Oct 25, 2020	3D Point Cloud ClassificationGeneral Classification	—Unverified
Empowering Local Communities Using Artificial Intelligence	Oct 5, 2021	Object Recognition	—Unverified
Enabling Pedestrian Safety using Computer Vision Techniques: A Case Study of the 2018 Uber Inc. Self-driving Car Crash	May 30, 2018	Image EnhancementObject Recognition	—Unverified

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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