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 1561–1570 of 2042 papers

Title	Date	Tasks	Status
Obtaining referential word meanings from visual and distributional information: Experiments on object naming	Jul 1, 2017	ObjectObject Recognition	—Unverified
Occluded Video Instance Segmentation: Dataset and ICCV 2021 Challenge	Nov 15, 2021	Instance SegmentationObject Recognition	—Unverified
Occlusion-aware Text-Image-Point Cloud Pretraining for Open-World 3D Object Recognition	Feb 15, 2025	3D Object RecognitionObject Recognition	—Unverified
Occlusion Boundary Detection via Deep Exploration of Context	Jun 1, 2016	Boundary DetectionObject Recognition	—Unverified
Occlusion Coherence: Localizing Occluded Faces with a Hierarchical Deformable Part Model	Jun 1, 2014	Face DetectionObject Recognition	—Unverified
OCTrack: Benchmarking the Open-Corpus Multi-Object Tracking	Jul 19, 2024	BenchmarkingMulti-Object Tracking	—Unverified
ODOR: The ICPR2022 ODeuropa Challenge on Olfactory Object Recognition	Jan 24, 2023	Domain AdaptationFew-Shot Learning	—Unverified
Offboard 3D Object Detection from Point Cloud Sequences	Mar 8, 2021	3D Object Detection3D Object Recognition	—Unverified
On Binary Classification with Single-Layer Convolutional Neural Networks	Sep 13, 2015	Binary ClassificationClassification	—Unverified
On-board classification of underwater images using hybrid classical-quantum CNN based method	Apr 19, 2024	Autonomous VehiclesGPU	—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