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 1371–1380 of 2042 papers

Title	Date	Tasks	Status	Hype
SqueezeJet: High-level Synthesis Accelerator Design for Deep Convolutional Neural Networks	May 6, 2018	High-Level Synthesisobject-detection	—Unverified	0
Object and Text-guided Semantics for CNN-based Activity Recognition	May 4, 2018	Activity RecognitionHuman Activity Recognition	—Unverified	0
SdcNet: A Computation-Efficient CNN for Object Recognition	May 3, 2018	ManagementObject	—Unverified	0
Unsupervised Learning using Pretrained CNN and Associative Memory Bank	May 2, 2018	Few-Shot Image ClassificationFine-Grained Image Classification	—Unverified	0
Semi-supervised Training Data Generation for Multilingual Question Answering	May 1, 2018	Machine TranslationNamed Entity Recognition (NER)	—Unverified	0
Incorporating Semantic Attention in Video Description Generation	May 1, 2018	Image CaptioningImage Classification	—Unverified	0
Dynamic Few-Shot Visual Learning without Forgetting	Apr 25, 2018	Few-Shot Image ClassificationFew-Shot Learning	CodeCode Available	1
MaskFusion: Real-Time Recognition, Tracking and Reconstruction of Multiple Moving Objects	Apr 24, 2018	ObjectObject Recognition	CodeCode Available	0
BrainSlug: Transparent Acceleration of Deep Learning Through Depth-First Parallelism	Apr 23, 2018	Deep LearningMachine Translation	—Unverified	0
Semantic Edge Detection with Diverse Deep Supervision	Apr 9, 2018	Edge DetectionObject Proposal Generation	CodeCode Available	0

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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