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 841–850 of 2042 papers

Title	Date	Tasks	Status
Generating Clear Images From Images With Distortions Caused by Adverse Weather Using Generative Adversarial Networks	Nov 1, 2022	Autonomous DrivingAutonomous Vehicles	—Unverified
Generating Image Descriptions with Gold Standard Visual Inputs: Motivation, Evaluation and Baselines	Sep 1, 2015	Image RetrievalObject Recognition	—Unverified
Comparing Data Sources and Architectures for Deep Visual Representation Learning in Semantics	Nov 1, 2016	Image RetrievalInformation Retrieval	—Unverified
Generative Model with Coordinate Metric Learning for Object Recognition Based on 3D Models	May 24, 2017	Bayesian InferenceMetric Learning	—Unverified
Are Accuracy and Robustness Correlated?	Oct 14, 2016	BIG-bench Machine LearningGeneral Classification	—Unverified
Exploring Temporal Differences in 3D Convolutional Neural Networks	Sep 7, 2019	image-classificationImage Classification	—Unverified
Exploring Context and Visual Pattern of Relationship for Scene Graph Generation	Jun 1, 2019	DiversityGraph Generation	—Unverified
GeoMag: A Vision-Language Model for Pixel-level Fine-Grained Remote Sensing Image Parsing	Jul 8, 2025	Language ModelingLanguage Modelling	—Unverified
Exploration of object recognition from 3D point cloud	Jul 5, 2017	ObjectObject Recognition	—Unverified
A randomized gradient-free attack on ReLU networks	Nov 28, 2018	Object 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