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 341–350 of 2042 papers

Title	Date	Tasks	Status
AI-Powered Augmented Reality for Satellite Assembly, Integration and Test	Sep 26, 2024	6D Pose EstimationObject Recognition	—Unverified
SeqNet: Sequential Networks for One-Shot Traffic Sign Recognition With Transfer Learning	Sep 23, 2024	Image RetrievalMetric Learning	CodeCode Available
Formula-Supervised Visual-Geometric Pre-training	Sep 20, 2024	3D Object Classification3D Object Recognition	—Unverified
A dynamic vision sensor object recognition model based on trainable event-driven convolution and spiking attention mechanism	Sep 19, 2024	Object Recognition	—Unverified
EventDance++: Language-guided Unsupervised Source-free Cross-modal Adaptation for Event-based Object Recognition	Sep 19, 2024	Object Recognition	—Unverified
Do Pre-trained Vision-Language Models Encode Object States?	Sep 16, 2024	Language ModelingLanguage Modelling	CodeCode Available
Benchmarking VLMs' Reasoning About Persuasive Atypical Images	Sep 16, 2024	BenchmarkingObject Recognition	—Unverified
Can Large Language Models Grasp Event Signals? Exploring Pure Zero-Shot Event-based Recognition	Sep 15, 2024	Object RecognitionZero-Shot Learning	CodeCode Available
Label Convergence: Defining an Upper Performance Bound in Object Recognition through Contradictory Annotations	Sep 14, 2024	Instance Segmentationobject-detection	CodeCode Available
Generalization Boosted Adapter for Open-Vocabulary Segmentation	Sep 13, 2024	Object RecognitionSegmentation	—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