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 261–270 of 2042 papers

Title	Date	Tasks	Status	Hype
ISCUTE: Instance Segmentation of Cables Using Text Embedding	Feb 19, 2024	Instance SegmentationObject Recognition	—Unverified	0
SpikeNAS: A Fast Memory-Aware Neural Architecture Search Framework for Spiking Neural Network-based Autonomous Agents	Feb 17, 2024	GPUNeural Architecture Search	—Unverified	0
Leveraging Self-Supervised Instance Contrastive Learning for Radar Object Detection	Feb 13, 2024	Contrastive LearningObject	—Unverified	0
A Benchmark Grocery Dataset of Realworld Point Clouds From Single View	Feb 12, 2024	3D Point Cloud ClassificationContinual Learning	—Unverified	0
Optimizing Sparse Convolution on GPUs with CUDA for 3D Point Cloud Processing in Embedded Systems	Feb 12, 2024	Object Recognition	—Unverified	0
Logical recognition method for solving the problem of identification in the Internet of Things	Feb 6, 2024	Object Recognition	—Unverified	0
A comparison between humans and AI at recognizing objects in unusual poses	Feb 6, 2024	Object Recognition	CodeCode Available	0
SHIELD : An Evaluation Benchmark for Face Spoofing and Forgery Detection with Multimodal Large Language Models	Feb 6, 2024	AttributeFace Anti-Spoofing	CodeCode Available	1
Motion Mapping Cognition: A Nondecomposable Primary Process in Human Vision	Feb 2, 2024	Image SegmentationObject Recognition	—Unverified	0
Lightweight Pixel Difference Networks for Efficient Visual Representation Learning	Feb 1, 2024	Edge DetectionObject Recognition	CodeCode Available	4

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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