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 561–570 of 2042 papers

Title	Date	Tasks	Status
3D Instance Segmentation Using Deep Learning on RGB-D Indoor Data	Jun 19, 2024	3D Instance Segmentation3D Object Recognition	—Unverified
Domain-robust VQA with diverse datasets and methods but no target labels	Mar 29, 2021	Domain AdaptationObject Recognition	—Unverified
DOZE: A Dataset for Open-Vocabulary Zero-Shot Object Navigation in Dynamic Environments	Feb 29, 2024	AttributeCollision Avoidance	—Unverified
Edge Aware Learning for 3D Point Cloud	Sep 23, 2023	ObjectObject Recognition	—Unverified
Catastrophic Child's Play: Easy to Perform, Hard to Defend Adversarial Attacks	Jun 1, 2019	Data AugmentationObject	—Unverified
Cascade Region Proposal and Global Context for Deep Object Detection	Oct 30, 2017	Objectobject-detection	—Unverified
An optical biomimetic eyes with interested object imaging	Aug 8, 2021	Deep LearningObject	—Unverified
A Non-Technical Survey on Deep Convolutional Neural Network Architectures	Mar 6, 2018	image-classificationImage Classification	—Unverified
Capturing the objects of vision with neural networks	Sep 7, 2021	ObjectObject Recognition	—Unverified
Adversarial Examples on Object Recognition: A Comprehensive Survey	Aug 7, 2020	BIG-bench Machine LearningObject	—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