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 671–680 of 2042 papers

Title	Date	Tasks	Status
Adaptive Active Learning for Image Classification	Jun 1, 2013	Active LearningClassification	—Unverified
CPWC: Contextual Point Wise Convolution for Object Recognition	Oct 21, 2019	ObjectObject Recognition	—Unverified
Counting the learnable functions of structured data	Mar 28, 2019	Object Recognition	—Unverified
Early or Late Fusion Matters: Efficient RGB-D Fusion in Vision Transformers for 3D Object Recognition	Oct 3, 2022	3D Object RecognitionLifelong learning	—Unverified
Co-training Transformer with Videos and Images Improves Action Recognition	Dec 14, 2021	Action ClassificationAction Recognition	—Unverified
A large comparison of feature-based approaches for buried target classification in forward-looking ground-penetrating radar	Feb 9, 2017	General ClassificationObject Recognition	—Unverified
CoTDet: Affordance Knowledge Prompting for Task Driven Object Detection	Sep 3, 2023	Objectobject-detection	—Unverified
Cost-Sensitive Deep Learning with Layer-Wise Cost Estimation	Nov 16, 2016	ClassificationDeep Learning	—Unverified
Assessing The Importance Of Colours For CNNs In Object Recognition	Dec 12, 2020	Fine-Grained Image ClassificationGeneral Classification	—Unverified
CortexNet: a Generic Network Family for Robust Visual Temporal Representations	Jun 8, 2017	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