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 1991–2000 of 2042 papers

Title	Date	Tasks	Status
Enhanced Multimodal RAG-LLM for Accurate Visual Question Answering	Dec 30, 2024	Image CaptioningObject Recognition	—Unverified
Enhancing 3D Object Detection in Autonomous Vehicles Based on Synthetic Virtual Environment Analysis	Dec 10, 2024	2D Object Detection3D Object Detection	—Unverified
Enhancing Crime Scene Investigations through Virtual Reality and Deep Learning Techniques	Sep 27, 2024	Object Recognition	—Unverified
Enhancing efficiency of object recognition in different categorization levels by reinforcement learning in modular spiking neural networks	Feb 10, 2021	Object Recognition	—Unverified
Enhancing Object Detection in Adverse Conditions using Thermal Imaging	Sep 30, 2019	Autonomous DrivingObject	—Unverified
Investigating the Role of Attribute Context in Vision-Language Models for Object Recognition and Detection	Mar 17, 2023	AttributeContrastive Learning	—Unverified
Enhancing Visual Representations for Efficient Object Recognition during Online Distillation	Jan 1, 2021	Object RecognitionOutlier Detection	—Unverified
Enlightening Deep Neural Networks with Knowledge of Confounding Factors	Jul 8, 2016	DisentanglementGeneral Classification	—Unverified
Enriched Deep Recurrent Visual Attention Model for Multiple Object Recognition	Jun 12, 2017	Object Recognition	—Unverified
Estimating Bicycle Route Attractivity from Image Data	Jun 27, 2018	Object RecognitionTransfer 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