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
PASTA: Proportional Amplitude Spectrum Training Augmentation for Syn-to-Real Domain Generalization	Dec 2, 2022	Domain Generalizationobject-detection	CodeCode Available	1
Learning Dense Object Descriptors from Multiple Views for Low-shot Category Generalization	Nov 28, 2022	Novel View SynthesisObject	CodeCode Available	1
Harmonizing the object recognition strategies of deep neural networks with humans	Nov 8, 2022	ObjectObject Recognition	CodeCode Available	1
Object Segmentation of Cluttered Airborne LiDAR Point Clouds	Oct 28, 2022	ObjectObject Recognition	CodeCode Available	1
AdaNorm: Adaptive Gradient Norm Correction based Optimizer for CNNs	Oct 12, 2022	Object Recognition	CodeCode Available	1
Improving ProtoNet for Few-Shot Video Object Recognition: Winner of ORBIT Challenge 2022	Oct 1, 2022	Few-Shot Image ClassificationObject Recognition	CodeCode Available	1
OBBStacking: An Ensemble Method for Remote Sensing Object Detection	Sep 27, 2022	Earth ObservationObject	CodeCode Available	1
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
Li-ion battery degradation modes diagnosis via Convolutional Neural Networks	Sep 24, 2022	Battery diagnosisObject Recognition	CodeCode Available	1
Visual Recognition with Deep Nearest Centroids	Sep 15, 2022	Decision Makingimage-classification	CodeCode Available	1

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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