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 1441–1450 of 2042 papers

Title	Date	Tasks	Status
Pointwise Convolutional Neural Networks	Dec 14, 2017	ObjectObject Recognition	CodeCode Available
Deep convolutional neural networks for brain image analysis on magnetic resonance imaging: a review	Dec 11, 2017	Lesion SegmentationMedical Image Analysis	—Unverified
Quantifying Translation-Invariance in Convolutional Neural Networks	Dec 10, 2017	Data AugmentationObject Recognition	—Unverified
Fine-Grained Object Recognition and Zero-Shot Learning in Remote Sensing Imagery	Dec 9, 2017	Language ModelingLanguage Modelling	—Unverified
Transformational Sparse Coding	Dec 8, 2017	ObjectObject Recognition	—Unverified
OLÉ: Orthogonal Low-rank Embedding, A Plug and Play Geometric Loss for Deep Learning	Dec 5, 2017	General Classificationimage-classification	CodeCode Available
Why my photos look sideways or upside down? Detecting Canonical Orientation of Images using Convolutional Neural Networks	Dec 4, 2017	Object RecognitionScene Understanding	—Unverified
Learning to Segment Moving Objects	Dec 1, 2017	Motion EstimationMotion Segmentation	—Unverified
Label Efficient Learning of Transferable Representations acrosss Domains and Tasks	Dec 1, 2017	Action RecognitionMetric Learning	—Unverified
Label Efficient Learning of Transferable Representations across Domains and Tasks	Nov 30, 2017	Action RecognitionMetric Learning	—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