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
Comics Datasets Framework: Mix of Comics datasets for detection benchmarking	Jul 3, 2024	BenchmarkingObject	CodeCode Available	1
The 3D-PC: a benchmark for visual perspective taking in humans and machines	Jun 6, 2024	Object Recognition	CodeCode Available	1
Bilateral Event Mining and Complementary for Event Stream Super-Resolution	May 16, 2024	Object RecognitionSuper-Resolution	CodeCode Available	1
Exploring the Transferability of Visual Prompting for Multimodal Large Language Models	Apr 17, 2024	HallucinationMultimodal Reasoning	CodeCode Available	1
Two Effects, One Trigger: On the Modality Gap, Object Bias, and Information Imbalance in Contrastive Vision-Language Models	Apr 11, 2024	AttributeObject	CodeCode Available	1
EventRPG: Event Data Augmentation with Relevance Propagation Guidance	Mar 14, 2024	Action RecognitionData Augmentation	CodeCode Available	1
MiKASA: Multi-Key-Anchor & Scene-Aware Transformer for 3D Visual Grounding	Mar 5, 2024	3D visual groundingDecision Making	CodeCode Available	1
CLoVe: Encoding Compositional Language in Contrastive Vision-Language Models	Feb 22, 2024	Object RecognitionRetrieval	CodeCode Available	1
SHIELD : An Evaluation Benchmark for Face Spoofing and Forgery Detection with Multimodal Large Language Models	Feb 6, 2024	AttributeFace Anti-Spoofing	CodeCode Available	1
Self-supervised learning of video representations from a child's perspective	Feb 1, 2024	Object RecognitionSelf-Supervised Learning	CodeCode Available	1

Show:10 25 50

← PrevPage 6 of 205Next →

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