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 211–220 of 1723 papers

Title	Date	Tasks	Status	Hype
Exploiting Edge-Oriented Reasoning for 3D Point-based Scene Graph Analysis	Mar 9, 2021	3d scene graph generationgraph construction	CodeCode Available	1
Boundary-induced and scene-aggregated network for monocular depth prediction	Feb 26, 2021	Depth EstimationDepth Prediction	CodeCode Available	1
EndoChat: Grounded Multimodal Large Language Model for Endoscopic Surgery	Jan 20, 2025	Language ModelingLanguage Modelling	CodeCode Available	1
Enhancing Scene Graph Generation with Hierarchical Relationships and Commonsense Knowledge	Nov 21, 2023	Large Language ModelMultimodal Deep Learning	CodeCode Available	1
CAKES: Channel-wise Automatic KErnel Shrinking for Efficient 3D Networks	Mar 28, 2020	3D Medical Imaging SegmentationAction Recognition	CodeCode Available	1
Joint 2D-3D-Semantic Data for Indoor Scene Understanding	Feb 3, 2017	Scene Understanding	CodeCode Available	1
Knowledge Distillation from 3D to Bird's-Eye-View for LiDAR Semantic Segmentation	Apr 22, 2023	Autonomous DrivingKnowledge Distillation	CodeCode Available	1
Lane Graph Estimation for Scene Understanding in Urban Driving	May 1, 2021	Autonomous DrivingAutonomous Vehicles	CodeCode Available	1
Language Embedded 3D Gaussians for Open-Vocabulary Scene Understanding	Nov 30, 2023	GPUInductive Bias	CodeCode Available	1
Exploring Data-Efficient 3D Scene Understanding with Contrastive Scene Contexts	Dec 16, 2020	3D Semantic SegmentationInstance Segmentation	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