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 1726–1750 of 2042 papers

Title	Date	Tasks	Status
Towards the Design of an End-to-End Automated System for Image and Video-based Recognition	Jan 28, 2016	Face VerificationObject	—Unverified
COCO-Text: Dataset and Benchmark for Text Detection and Recognition in Natural Images	Jan 26, 2016	DiversityGeneral Classification	CodeCode Available
The Image Torque Operator for Contour Processing	Jan 18, 2016	Edge DetectionImage Description	—Unverified
Face-space Action Recognition by Face-Object Interactions	Jan 17, 2016	Action RecognitionAction Recognition In Still Images	—Unverified
Deep Neural Networks predict Hierarchical Spatio-temporal Cortical Dynamics of Human Visual Object Recognition	Jan 12, 2016	Object Recognition	—Unverified
Kernel principal component analysis network for image classification	Dec 20, 2015	ClassificationFace Recognition	—Unverified
Poseidon: A System Architecture for Efficient GPU-based Deep Learning on Multiple Machines	Dec 19, 2015	CPUGPU	—Unverified
Deep Active Object Recognition by Joint Label and Action Prediction	Dec 17, 2015	ObjectObject Recognition	—Unverified
Origami: A 803 GOp/s/W Convolutional Network Accelerator	Dec 14, 2015	Action RecognitionObject Recognition	—Unverified
Fine-grained Image Classification by Exploring Bipartite-Graph Labels	Dec 8, 2015	ClassificationFine-Grained Image Classification	—Unverified
What can we learn about CNNs from a large scale controlled object dataset?	Dec 4, 2015	Domain AdaptationObject Recognition	—Unverified
Infinite Feature Selection	Dec 1, 2015	Classificationfeature selection	CodeCode Available
Query Adaptive Similarity Measure for RGB-D Object Recognition	Dec 1, 2015	ObjectObject Recognition	—Unverified
SALICON: Reducing the Semantic Gap in Saliency Prediction by Adapting Deep Neural Networks	Dec 1, 2015	Object RecognitionSaliency Prediction	—Unverified
MMSS: Multi-Modal Sharable and Specific Feature Learning for RGB-D Object Recognition	Dec 1, 2015	ObjectObject Recognition	—Unverified
RIDE: Reversal Invariant Descriptor Enhancement	Dec 1, 2015	Object Recognition	—Unverified
HD-CNN: Hierarchical Deep Convolutional Neural Networks for Large Scale Visual Recognition	Dec 1, 2015	image-classificationImage Classification	—Unverified
Learning to Combine Mid-Level Cues for Object Proposal Generation	Dec 1, 2015	Object Proposal GenerationObject Recognition	—Unverified
Augmenting Strong Supervision Using Web Data for Fine-Grained Categorization	Dec 1, 2015	Object Recognition	—Unverified
Unsupervised Generation of a Viewpoint Annotated Car Dataset From Videos	Dec 1, 2015	ObjectObject Recognition	—Unverified
Hierarchical Convolutional Features for Visual Tracking	Dec 1, 2015	Object RecognitionObject Tracking	—Unverified
Convolutional Neural Networks with Intra-Layer Recurrent Connections for Scene Labeling	Dec 1, 2015	Object RecognitionScene Labeling	—Unverified
Recursive Training of 2D-3D Convolutional Networks for Neuronal Boundary Prediction	Dec 1, 2015	3D ArchitectureBoundary Detection	—Unverified
Feature-based Attention in Convolutional Neural Networks	Nov 19, 2015	Objectobject-detection	—Unverified
Deep Compositional Captioning: Describing Novel Object Categories without Paired Training Data	Nov 17, 2015	Image CaptioningNovel Concepts	CodeCode Available

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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