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 751–775 of 2042 papers

Title	Date	Tasks	Status	Hype
VDM-DA: Virtual Domain Modeling for Source Data-free Domain Adaptation	Mar 26, 2021	Domain AdaptationObject Recognition	—Unverified	0
Projection: A Mechanism for Human-like Reasoning in Artificial Intelligence	Mar 24, 2021	Object Recognition	—Unverified	0
DNN Quantization with Attention	Mar 24, 2021	Object RecognitionQuantization	—Unverified	0
Contrastive Reasoning in Neural Networks	Mar 23, 2021	Object Recognition	—Unverified	0
F-SIOL-310: A Robotic Dataset and Benchmark for Few-Shot Incremental Object Learning	Mar 23, 2021	Incremental LearningObject	CodeCode Available	1
Neural Networks for Semantic Gaze Analysis in XR Settings	Mar 18, 2021	Image AugmentationObject Recognition	—Unverified	0
Hebbian Semi-Supervised Learning in a Sample Efficiency Setting	Mar 16, 2021	Object Recognition	—Unverified	0
Towards Learning Food Portion From Monocular Images With Cross-Domain Feature Adaptation	Mar 12, 2021	Image SegmentationManagement	—Unverified	0
PatchNet -- Short-range Template Matching for Efficient Video Processing	Mar 10, 2021	Objectobject-detection	CodeCode Available	1
Structure-From-Motion and RGBD Depth Fusion	Mar 10, 2021	Object Recognition	—Unverified	0
A Study of Face Obfuscation in ImageNet	Mar 10, 2021	AttributeObject	CodeCode Available	1
Point Cloud Sampling via Graph Balancing and Gershgorin Disc Alignment	Mar 10, 2021	Graph SamplingObject Recognition	—Unverified	0
FAIR1M: A Benchmark Dataset for Fine-grained Object Recognition in High-Resolution Remote Sensing Imagery	Mar 9, 2021	Deep LearningObject	CodeCode Available	1
A Discriminative Vectorial Framework for Multi-modal Feature Representation	Mar 9, 2021	Audio Emotion RecognitionData Visualization	—Unverified	0
Contemplating real-world object classification	Mar 8, 2021	ClassificationData Augmentation	CodeCode Available	1
Offboard 3D Object Detection from Point Cloud Sequences	Mar 8, 2021	3D Object Detection3D Object Recognition	—Unverified	0
Deep Clustering by Semantic Contrastive Learning	Mar 3, 2021	ClusteringContrastive Learning	—Unverified	0
Cooking Object's State Identification Without Using Pretrained Model	Mar 3, 2021	modelObject	—Unverified	0
Domain Generalization: A Survey	Mar 3, 2021	Action RecognitionData Augmentation	—Unverified	0
A Multiclass Boosting Framework for Achieving Fast and Provable Adversarial Robustness	Mar 1, 2021	Adversarial RobustnessObject Recognition	—Unverified	0
Self-Supervised Multi-View Learning via Auto-Encoding 3D Transformations	Mar 1, 2021	3D Object Classification3D Object Recognition	—Unverified	0
The Labeled Multiple Canonical Correlation Analysis for Information Fusion	Feb 28, 2021	Emotion RecognitionFace Recognition	—Unverified	0
Achieving Competitive Play Through Bottom-Up Approach in Semantic Segmentation	Feb 28, 2021	Objectobject-detection	—Unverified	0
Learning Transferable Visual Models From Natural Language Supervision	Feb 26, 2021	Action RecognitionBenchmarking	CodeCode Available	2
CausalX: Causal Explanations and Block Multilinear Factor Analysis	Feb 25, 2021	Computational Efficiencycounterfactual	—Unverified	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