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 91–100 of 2042 papers

Title	Date	Tasks	Status	Hype	Score
CLoVe: Encoding Compositional Language in Contrastive Vision-Language Models	Feb 22, 2024	Object RecognitionRetrieval	CodeCode Available	1	5
Rehearsal-Free Continual Learning over Small Non-I.I.D. Batches	Jul 8, 2019	class-incremental learningClass Incremental Learning	CodeCode Available	1	5
CLIP-guided Federated Learning on Heterogeneous and Long-Tailed Data	Dec 14, 2023	Contrastive LearningFederated Learning	CodeCode Available	1	5
From Chaos Comes Order: Ordering Event Representations for Object Recognition and Detection	Apr 26, 2023	Event-based visionobject-detection	CodeCode Available	1	5
Attribution in Scale and Space	Apr 3, 2020	AttributeObject Recognition	CodeCode Available	1	5
Divergences in Color Perception between Deep Neural Networks and Humans	Sep 11, 2023	image-classificationImage Classification	CodeCode Available	1	5
Comics Datasets Framework: Mix of Comics datasets for detection benchmarking	Jul 3, 2024	BenchmarkingObject	CodeCode Available	1	5
Compact Generalized Non-local Network	Oct 31, 2018	Object DetectionObject Recognition	CodeCode Available	1	5
3D ShapeNets: A Deep Representation for Volumetric Shapes	Jun 22, 2014	3D Point Cloud Classification3D Shape Representation	CodeCode Available	1	5
Doubly Right Object Recognition: A Why Prompt for Visual Rationales	Dec 12, 2022	Object Recognition	CodeCode Available	1	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