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 301–325 of 2042 papers

Title	Date	Tasks	Status	Score
Investigating the Gestalt Principle of Closure in Deep Convolutional Neural Networks	Nov 1, 2024	Object Recognition	CodeCode Available	5
AGA: Attribute-Guided Augmentation	Jul 1, 2017	AttributeData Augmentation	CodeCode Available	5
GAANet: Ghost Auto Anchor Network for Detecting Varying Size Drones in Dark	May 5, 2023	Objectobject-detection	CodeCode Available	5
AGA: Attribute Guided Augmentation	Dec 8, 2016	AttributeData Augmentation	CodeCode Available	5
FPNN: Field Probing Neural Networks for 3D Data	May 20, 2016	3D geometry3D Object Recognition	CodeCode Available	5
A Framework of Transfer Learning in Object Detection for Embedded Systems	Nov 12, 2018	Hyperparameter OptimizationObject	CodeCode Available	5
Foveated Instance Segmentation	Mar 27, 2025	Instance SegmentationObject Recognition	CodeCode Available	5
Foveation in the Era of Deep Learning	Dec 3, 2023	Deep LearningFoveation	CodeCode Available	5
Generalisation in humans and deep neural networks	Aug 27, 2018	Object Recognition	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
A Probabilistic Theory of Deep Learning	Apr 2, 2015	Deep LearningObject	CodeCode Available	5
Fit to Measure: Reasoning about Sizes for Robust Object Recognition	Oct 27, 2020	BIG-bench Machine LearningObject	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
A Computational Acquisition Model for Multimodal Word Categorization	May 12, 2022	Language Acquisitionmodel	CodeCode Available	5
Food Image Recognition by Using Convolutional Neural Networks (CNNs)	Dec 3, 2016	Data AugmentationGeneral Classification	CodeCode Available	5
Feature Pyramid Grids	Apr 7, 2020	Neural Architecture Searchobject-detection	CodeCode Available	5
Feature Learning for Accelerometer based Gait Recognition	Jul 31, 2020	Gait RecognitionObject Recognition	CodeCode Available	5
FewSOL: A Dataset for Few-Shot Object Learning in Robotic Environments	Jul 6, 2022	AttributeClassification	CodeCode Available	5
Fast Feature Fool: A data independent approach to universal adversarial perturbations	Jul 18, 2017	Object Recognition	CodeCode Available	5
Context-Aware Zero-Shot Recognition	Apr 19, 2019	Object RecognitionZero-Shot Learning	CodeCode Available	5
Feature Learning by Multidimensional Scaling and its Applications in Object Recognition	Jun 14, 2013	Object Recognition	CodeCode Available	5
Finding Tiny Faces	Dec 13, 2016	Face DetectionObject 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
Exploring Novel Object Recognition and Spontaneous Location Recognition Machine Learning Analysis Techniques in Alzheimer's Mice	Dec 12, 2023	Object RecognitionPose Estimation	CodeCode Available	5
Facial Expression Recognition Research Based on Deep Learning	Apr 22, 2019	Deep LearningFacial Expression Recognition	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