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 741–750 of 2042 papers

Title	Date	Tasks	Status
A randomized gradient-free attack on ReLU networks	Nov 28, 2018	Object Recognition	—Unverified
Exploring Temporal Differences in 3D Convolutional Neural Networks	Sep 7, 2019	image-classificationImage Classification	—Unverified
The Origins and Prevalence of Texture Bias in Convolutional Neural Networks	Nov 20, 2019	Data AugmentationObject Recognition	—Unverified
Feature Evaluation of Deep Convolutional Neural Networks for Object Recognition and Detection	Sep 25, 2015	General ClassificationObject Recognition	—Unverified
Exponential Discriminative Metric Embedding in Deep Learning	Mar 7, 2018	Deep LearningFace Recognition	—Unverified
Extreme Image Transformations Affect Humans and Machines Differently	Nov 30, 2022	Object Recognition	—Unverified
Extreme Image Transformations Facilitate Robust Latent Object Representations	Sep 19, 2023	feature selectionMemorization	—Unverified
EZSR: Event-based Zero-Shot Recognition	Jul 31, 2024	ObjectObject Recognition	—Unverified
Fabric Surface Characterization: Assessment of Deep Learning-based Texture Representations Using a Challenging Dataset	Mar 16, 2020	Material RecognitionObject Recognition	—Unverified
Disentangling Properties of Contrastive Methods	Sep 29, 2021	DisentanglementObject 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