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
A Review of Panoptic Segmentation for Mobile Mapping Point Clouds	Apr 27, 2023	Instance SegmentationPanoptic Segmentation	CodeCode Available	1
Estimating and Exploiting the Aleatoric Uncertainty in Surface Normal Estimation	Sep 20, 2021	DecoderPrediction	CodeCode Available	1
Event-aided Semantic Scene Completion	Feb 4, 2025	Autonomous DrivingScene Understanding	CodeCode Available	1
Event-based Motion Segmentation with Spatio-Temporal Graph Cuts	Dec 16, 2020	Motion SegmentationScene Understanding	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
Exploring Data-Efficient 3D Scene Understanding with Contrastive Scene Contexts	Dec 16, 2020	3D Semantic SegmentationInstance Segmentation	CodeCode Available	1
Enhancing Scene Graph Generation with Hierarchical Relationships and Commonsense Knowledge	Nov 21, 2023	Large Language ModelMultimodal Deep Learning	CodeCode Available	1
Advances in Deep Concealed Scene Understanding	Apr 21, 2023	Scene UnderstandingSemantic Segmentation	CodeCode Available	1
Estimating Generic 3D Room Structures from 2D Annotations	Jun 15, 2023	Scene Understanding	CodeCode Available	1
A2-FPN for Semantic Segmentation of Fine-Resolution Remotely Sensed Images	Feb 16, 2021	Decision MakingScene Understanding	CodeCode Available	1

Show:10 25 50

← PrevPage 13 of 173Next →

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