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 581–590 of 2042 papers

Title	Date	Tasks	Status
Shift from Texture-bias to Shape-bias: Edge Deformation-based Augmentation for Robust Object Recognition	Jan 1, 2023	Object Recognition	—Unverified
Autonomous Manipulation Learning for Similar Deformable Objects via Only One Demonstration	Jan 1, 2023	Deformable Object ManipulationObject	—Unverified
MISC210K: A Large-Scale Dataset for Multi-Instance Semantic Correspondence	Jan 1, 2023	ObjectObject Recognition	CodeCode Available
Parsing Objects at a Finer Granularity: A Survey	Dec 28, 2022	Fine-Grained Visual RecognitionHuman Part Segmentation	—Unverified
Brain Cancer Segmentation Using YOLOv5 Deep Neural Network	Dec 27, 2022	GPUInstance Segmentation	—Unverified
Decision-making and control with diffractive optical networks	Dec 21, 2022	Autonomous DrivingCar Racing	CodeCode Available
Improving Pre-Trained Weights Through Meta-Heuristics Fine-Tuning	Dec 19, 2022	image-classificationImage Classification	CodeCode Available
ColorSense: A Study on Color Vision in Machine Visual Recognition	Dec 16, 2022	Data AugmentationObject Recognition	—Unverified
OAMixer: Object-aware Mixing Layer for Vision Transformers	Dec 13, 2022	Inductive BiasObject	CodeCode Available
A novel feature-scrambling approach reveals the capacity of convolutional neural networks to learn spatial relations	Dec 12, 2022	ObjectObject Recognition	—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