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 121–130 of 1723 papers

Title	Date	Tasks	Status	Hype	Score
A Review of Panoptic Segmentation for Mobile Mapping Point Clouds	Apr 27, 2023	Instance SegmentationPanoptic Segmentation	CodeCode Available	1	5
Explainable Object-induced Action Decision for Autonomous Vehicles	Mar 20, 2020	Autonomous DrivingAutonomous Vehicles	CodeCode Available	1	5
CoPeD-Advancing Multi-Robot Collaborative Perception: A Comprehensive Dataset in Real-World Environments	May 23, 2024	Pose EstimationScene Understanding	CodeCode Available	1	5
Exploring Data-Efficient 3D Scene Understanding with Contrastive Scene Contexts	Dec 16, 2020	3D Semantic SegmentationInstance Segmentation	CodeCode Available	1	5
CPCM: Contextual Point Cloud Modeling for Weakly-supervised Point Cloud Semantic Segmentation	Jul 19, 2023	Representation LearningScene Understanding	CodeCode Available	1	5
Context Prior for Scene Segmentation	Apr 3, 2020	Scene SegmentationScene Understanding	CodeCode Available	1	5
Advances in Deep Concealed Scene Understanding	Apr 21, 2023	Scene UnderstandingSemantic Segmentation	CodeCode Available	1	5
Event-based Motion Segmentation with Spatio-Temporal Graph Cuts	Dec 16, 2020	Motion SegmentationScene Understanding	CodeCode Available	1	5
Exploiting Edge-Oriented Reasoning for 3D Point-based Scene Graph Analysis	Mar 9, 2021	3d scene graph generationgraph construction	CodeCode Available	1	5
A2-FPN for Semantic Segmentation of Fine-Resolution Remotely Sensed Images	Feb 16, 2021	Decision MakingScene Understanding	CodeCode Available	1	5

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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