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 1–10 of 2042 papers

Title	Date	Tasks	Status	Hype
Lightweight Pixel Difference Networks for Efficient Visual Representation Learning	Feb 1, 2024	Edge DetectionObject Recognition	CodeCode Available	4
RTMDet: An Empirical Study of Designing Real-Time Object Detectors	Dec 14, 2022	GPUInstance Segmentation	CodeCode Available	4
Detectron2 Object Detection & Manipulating Images using Cartoonization	Aug 1, 2021	Autonomous VehiclesData Visualization	CodeCode Available	4
Interactive Medical Image Segmentation: A Benchmark Dataset and Baseline	Nov 19, 2024	Image SegmentationInteractive Segmentation	CodeCode Available	3
UniBench: Visual Reasoning Requires Rethinking Vision-Language Beyond Scaling	Aug 9, 2024	GPULanguage Modeling	CodeCode Available	3
pix2gestalt: Amodal Segmentation by Synthesizing Wholes	Jan 25, 2024	3D ReconstructionObject Recognition	CodeCode Available	3
DALL-Eval: Probing the Reasoning Skills and Social Biases of Text-to-Image Generation Models	Feb 8, 2022	DiagnosticImage Captioning	CodeCode Available	3
Datasets: A Community Library for Natural Language Processing	Sep 7, 2021	Image ClassificationObject Recognition	CodeCode Available	3
InstructSAM: A Training-Free Framework for Instruction-Oriented Remote Sensing Object Recognition	May 21, 2025	Earth ObservationObject	CodeCode Available	2
Taccel: Scaling Up Vision-based Tactile Robotics via High-performance GPU Simulation	Apr 17, 2025	GPUObject Recognition	CodeCode Available	2

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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