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 51–60 of 2042 papers

Title	Date	Tasks	Status	Hype	Score
Benchmarking Multimodal Mathematical Reasoning with Explicit Visual Dependency	Apr 24, 2025	BenchmarkingMath	CodeCode Available	1	5
Discover and Cure: Concept-aware Mitigation of Spurious Correlation	May 1, 2023	Lesion ClassificationObject Recognition	CodeCode Available	1	5
Adapting Self-Supervised Vision Transformers by Probing Attention-Conditioned Masking Consistency	Jun 16, 2022	Domain AdaptationObject Recognition	CodeCode Available	1	5
Attribution in Scale and Space	Apr 3, 2020	AttributeObject Recognition	CodeCode Available	1	5
Brain-Score: Which Artificial Neural Network for Object Recognition is most Brain-Like?	Jan 2, 2020	Object Recognition	CodeCode Available	1	5
Domain Generalization for Object Recognition with Multi-task Autoencoders	Aug 31, 2015	DenoisingDomain Generalization	CodeCode Available	1	5
Bilateral Event Mining and Complementary for Event Stream Super-Resolution	May 16, 2024	Object RecognitionSuper-Resolution	CodeCode Available	1	5
Billion-scale semi-supervised learning for image classification	May 2, 2019	ClassificationGeneral Classification	CodeCode Available	1	5
BURST: A Benchmark for Unifying Object Recognition, Segmentation and Tracking in Video	Sep 25, 2022	Long-tail Video Object SegmentationMulti-Object Tracking	CodeCode Available	1	5
Deep Subdomain Adaptation Network for Image Classification	Jun 17, 2021	ClassificationDomain Adaptation	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