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 271–280 of 2042 papers

Title	Date	Tasks	Status	Score
GAANet: Ghost Auto Anchor Network for Detecting Varying Size Drones in Dark	May 5, 2023	Objectobject-detection	CodeCode Available	5
Geometric and Textural Augmentation for Domain Gap Reduction	Jan 1, 2022	ObjectObject Recognition	CodeCode Available	5
FoodTracker: A Real-time Food Detection Mobile Application by Deep Convolutional Neural Networks	Sep 13, 2019	NutritionObject Recognition	CodeCode Available	5
Foveated Instance Segmentation	Mar 27, 2025	Instance SegmentationObject Recognition	CodeCode Available	5
Adapting Deep Network Features to Capture Psychological Representations	Aug 6, 2016	Object RecognitionScene Understanding	CodeCode Available	5
Food Image Recognition by Using Convolutional Neural Networks (CNNs)	Dec 3, 2016	Data AugmentationGeneral Classification	CodeCode Available	5
Foveation in the Era of Deep Learning	Dec 3, 2023	Deep LearningFoveation	CodeCode Available	5
Enhancing Fine-Grained 3D Object Recognition using Hybrid Multi-Modal Vision Transformer-CNN Models	Oct 3, 2022	3D Object RecognitionFine-Grained Image Classification	CodeCode Available	5
Finding Tiny Faces	Dec 13, 2016	Face DetectionObject Recognition	CodeCode Available	5
Fine-grained Attention and Feature-sharing Generative Adversarial Networks for Single Image Super-Resolution	Nov 25, 2019	Generative Adversarial NetworkImage Super-Resolution	CodeCode Available	5

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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