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 221–230 of 2042 papers

Title	Date	Tasks	Status	Hype
CloudFort: Enhancing Robustness of 3D Point Cloud Classification Against Backdoor Attacks via Spatial Partitioning and Ensemble Prediction	Apr 22, 2024	3D Point Cloud ClassificationAutonomous Vehicles	—Unverified	0
On-board classification of underwater images using hybrid classical-quantum CNN based method	Apr 19, 2024	Autonomous VehiclesGPU	—Unverified	0
ECOR: Explainable CLIP for Object Recognition	Apr 19, 2024	Objectobject-detection	—Unverified	0
How to deal with glare for improved perception of Autonomous Vehicles	Apr 17, 2024	Autonomous DrivingAutonomous Vehicles	—Unverified	0
Achieving Rotation Invariance in Convolution Operations: Shifting from Data-Driven to Mechanism-Assured	Apr 17, 2024	Data Augmentationimage-classification	—Unverified	0
Exploring the Transferability of Visual Prompting for Multimodal Large Language Models	Apr 17, 2024	HallucinationMultimodal Reasoning	CodeCode Available	1
A Diffusion-based Data Generator for Training Object Recognition Models in Ultra-Range Distance	Apr 15, 2024	Gesture RecognitionObject Recognition	—Unverified	0
Two Effects, One Trigger: On the Modality Gap, Object Bias, and Information Imbalance in Contrastive Vision-Language Models	Apr 11, 2024	AttributeObject	CodeCode Available	1
A Dataset and Framework for Learning State-invariant Object Representations	Apr 9, 2024	ObjectObject Recognition	CodeCode Available	0
MindSet: Vision. A toolbox for testing DNNs on key psychological experiments	Apr 8, 2024	DecoderObject Recognition	CodeCode Available	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