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 1751–1775 of 2042 papers

Title	Date	Tasks	Status
Recursive Training of 2D-3D Convolutional Networks for Neuronal Boundary Prediction	Dec 1, 2015	3D ArchitectureBoundary Detection	—Unverified
HD-CNN: Hierarchical Deep Convolutional Neural Networks for Large Scale Visual Recognition	Dec 1, 2015	image-classificationImage Classification	—Unverified
MMSS: Multi-Modal Sharable and Specific Feature Learning for RGB-D Object Recognition	Dec 1, 2015	ObjectObject Recognition	—Unverified
Convolutional Neural Networks with Intra-Layer Recurrent Connections for Scene Labeling	Dec 1, 2015	Object RecognitionScene Labeling	—Unverified
Unsupervised Generation of a Viewpoint Annotated Car Dataset From Videos	Dec 1, 2015	ObjectObject Recognition	—Unverified
Augmenting Strong Supervision Using Web Data for Fine-Grained Categorization	Dec 1, 2015	Object Recognition	—Unverified
Hierarchical Convolutional Features for Visual Tracking	Dec 1, 2015	Object RecognitionObject Tracking	—Unverified
Query Adaptive Similarity Measure for RGB-D Object Recognition	Dec 1, 2015	ObjectObject Recognition	—Unverified
RIDE: Reversal Invariant Descriptor Enhancement	Dec 1, 2015	Object Recognition	—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
Convolutional Models for Joint Object Categorization and Pose Estimation	Nov 16, 2015	ObjectObject Categorization	—Unverified
Basic Level Categorization Facilitates Visual Object Recognition	Nov 12, 2015	ObjectObject Categorization	—Unverified
Hand-Object Interaction and Precise Localization in Transitive Action Recognition	Nov 12, 2015	Action RecognitionAction Recognition In Still Images	—Unverified
Multimodal Skip-gram Using Convolutional Pseudowords	Nov 12, 2015	Object RecognitionRetrieval	—Unverified
Visual7W: Grounded Question Answering in Images	Nov 11, 2015	Multiple-choiceMultiple Choice Question Answering (MCQA)	—Unverified
Semantic Instance Annotation of Street Scenes by 3D to 2D Label Transfer	Nov 10, 2015	Object RecognitionScene Understanding	—Unverified
Deep Sliding Shapes for Amodal 3D Object Detection in RGB-D Images	Nov 7, 2015	3D Object DetectionObject	—Unverified
Pixel-wise Segmentation of Street with Neural Networks	Nov 2, 2015	Object Recognitionregression	—Unverified
Regional Active Contours based on Variational level sets and Machine Learning for Image Segmentation	Oct 31, 2015	BIG-bench Machine LearningImage Segmentation	—Unverified
Fast Neuromimetic Object Recognition using FPGA Outperforms GPU Implementations	Oct 31, 2015	GPUObject	—Unverified
Generic decoding of seen and imagined objects using hierarchical visual features	Oct 22, 2015	DecoderInformation Retrieval	—Unverified
PERCH: Perception via Search for Multi-Object Recognition and Localization	Oct 19, 2015	Heuristic SearchObject Recognition	—Unverified
Scatter Component Analysis: A Unified Framework for Domain Adaptation and Domain Generalization	Oct 15, 2015	Domain AdaptationDomain Generalization	—Unverified
Better Exploiting OS-CNNs for Better Event Recognition in Images	Oct 14, 2015	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