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
Proactive Adversarial Defense: Harnessing Prompt Tuning in Vision-Language Models to Detect Unseen Backdoored Images	Dec 11, 2024	Adversarial Defensebackdoor defense	—Unverified	0
Enhancing 3D Object Detection in Autonomous Vehicles Based on Synthetic Virtual Environment Analysis	Dec 10, 2024	2D Object Detection3D Object Detection	—Unverified	0
Can foundation models actively gather information in interactive environments to test hypotheses?	Dec 9, 2024	Object Recognition	—Unverified	0
Expanding Event Modality Applications through a Robust CLIP-Based Encoder	Dec 4, 2024	Few-Shot LearningObject Recognition	CodeCode Available	1
Optimized CNNs for Rapid 3D Point Cloud Object Recognition	Dec 3, 2024	Computational Efficiencyobject-detection	—Unverified	0
LVLM-COUNT: Enhancing the Counting Ability of Large Vision-Language Models	Dec 1, 2024	Object Recognition	CodeCode Available	0
Textured As-Is BIM via GIS-informed Point Cloud Segmentation	Nov 28, 2024	Object RecognitionPoint Cloud Segmentation	—Unverified	0
Verbalized Representation Learning for Interpretable Few-Shot Generalization	Nov 27, 2024	Language ModelingLanguage Modelling	CodeCode Available	0
Grid-augmented vision: A simple yet effective approach for enhanced spatial understanding in multi-modal agents	Nov 27, 2024	Autonomous NavigationObject Recognition	CodeCode Available	0
NEMO: Can Multimodal LLMs Identify Attribute-Modified Objects?	Nov 26, 2024	AttributeMultiple-choice	—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