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 441–450 of 2042 papers

Title	Date	Tasks	Status	Score
Dynamic Rectification Knowledge Distillation	Jan 27, 2022	Edge-computingKnowledge Distillation	CodeCode Available	5
EBPC: Extended Bit-Plane Compression for Deep Neural Network Inference and Training Accelerators	Aug 30, 2019	image-classificationImage Classification	CodeCode Available	5
A Classification approach towards Unsupervised Learning of Visual Representations	Jun 1, 2018	ClassificationGeneral Classification	CodeCode Available	5
Breast Cancer Classification from Histopathological Images with Inception Recurrent Residual Convolutional Neural Network	Nov 10, 2018	Cancer ClassificationClassification	CodeCode Available	5
Efficient Event Stream Super-Resolution with Recursive Multi-Branch Fusion	Jun 28, 2024	Object RecognitionSuper-Resolution	CodeCode Available	5
DAAL: Density-Aware Adaptive Line Margin Loss for Multi-Modal Deep Metric Learning	Oct 7, 2024	Face VerificationMetric Learning	CodeCode Available	5
Don't Judge by the Look: Towards Motion Coherent Video Representation	Mar 14, 2024	Data AugmentationObject Recognition	CodeCode Available	5
Training Deep Neural Networks via Branch-and-Bound	Apr 5, 2021	Object RecognitionStochastic Optimization	CodeCode Available	5
Do Pre-trained Vision-Language Models Encode Object States?	Sep 16, 2024	Language ModelingLanguage Modelling	CodeCode Available	5
Domain Generalization via Model-Agnostic Learning of Semantic Features	Oct 29, 2019	Domain GeneralizationGeneral Knowledge	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