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 291–300 of 1723 papers

Title	Date	Tasks	Status	Hype
Affordance Transfer Learning for Human-Object Interaction Detection	Apr 7, 2021	Affordance DetectionAffordance Recognition	CodeCode Available	1
FreDSNet: Joint Monocular Depth and Semantic Segmentation with Fast Fourier Convolutions	Oct 4, 2022	Depth EstimationMonocular Depth Estimation	CodeCode Available	1
GOV-NeSF: Generalizable Open-Vocabulary Neural Semantic Fields	Apr 1, 2024	Open Vocabulary Semantic SegmentationOpen-Vocabulary Semantic Segmentation	CodeCode Available	1
From Multi-View to Hollow-3D: Hallucinated Hollow-3D R-CNN for 3D Object Detection	Jul 30, 2021	3D Object Detectionobject-detection	CodeCode Available	1
HiLo: Exploiting High Low Frequency Relations for Unbiased Panoptic Scene Graph Generation	Mar 28, 2023	Panoptic Scene Graph GenerationScene Graph Generation	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
A Survey on Deep Learning Technique for Video Segmentation	Jul 2, 2021	Autonomous DrivingDeep Learning	CodeCode Available	1
Exploring Data-Efficient 3D Scene Understanding with Contrastive Scene Contexts	Dec 16, 2020	3D Semantic SegmentationInstance Segmentation	CodeCode Available	1
4D Panoptic LiDAR Segmentation	Feb 24, 2021	4D Panoptic SegmentationBenchmarking	CodeCode Available	1
Explainable Object-induced Action Decision for Autonomous Vehicles	Mar 20, 2020	Autonomous DrivingAutonomous Vehicles	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