Scene Understanding

Scene understanding involves interpreting the visual information of a scene, including objects, their spatial relationships, and the overall layout. It goes beyond simple object recognition by considering the context and how objects relate to each other and the environment.

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 181–190 of 1723 papers

Title	Date	Tasks	Status	Hype
Explainable Object-induced Action Decision for Autonomous Vehicles	Mar 20, 2020	Autonomous DrivingAutonomous Vehicles	CodeCode Available	1
Exploiting Edge-Oriented Reasoning for 3D Point-based Scene Graph Analysis	Mar 9, 2021	3d scene graph generationgraph construction	CodeCode Available	1
Bending Reality: Distortion-aware Transformers for Adapting to Panoramic Semantic Segmentation	Mar 2, 2022	Domain AdaptationScene Understanding	CodeCode Available	1
BEVDistill: Cross-Modal BEV Distillation for Multi-View 3D Object Detection	Nov 17, 2022	3D Object DetectionDepth Estimation	CodeCode Available	1
Beyond Appearances: Material Segmentation with Embedded Spectral Information from RGB-D imagery	May 17, 2024	Material ClassificationMaterial Recognition	CodeCode Available	1
AVSegFormer: Audio-Visual Segmentation with Transformer	Jul 3, 2023	DecoderScene Understanding	CodeCode Available	1
Efficient Multi-Task RGB-D Scene Analysis for Indoor Environments	Jul 10, 2022	Instance SegmentationPanoptic Segmentation	CodeCode Available	1
Activation Modulation and Recalibration Scheme for Weakly Supervised Semantic Segmentation	Dec 16, 2021	Feature ImportanceScene Understanding	CodeCode Available	1
Dynamic Graph Message Passing Networks for Visual Recognition	Sep 20, 2022	image-classificationImage Classification	CodeCode Available	1
Dynamic Graph Message Passing Networks	Aug 19, 2019	Image Classificationobject-detection	CodeCode Available	1

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All datasets Semantic Scene Understanding Challenge (passive actuation & ground-truth localisation)ADE20K val Semantic Scene Understanding Challenge (active actuation & ground-truth localisation)

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	ACRV Baseline	OMQ	0.44	—	Unverified
2	Team VGAI (TCS Research)	OMQ	0.37	—	Unverified
3	Demo_semantic_SLAM	OMQ	0.11	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	CPN(ResNet-101)	Mean IoU	46.3	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	ACRV Baseline	OMQ	0.35	—	Unverified