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 491–500 of 1723 papers

Title	Date	Tasks	Status	Score
Part-Whole Relational Fusion Towards Multi-Modal Scene Understanding	Oct 19, 2024	Autonomous Drivingobject-detection	CodeCode Available	5
Parsing Geometry Using Structure-Aware Shape Templates	Aug 3, 2018	ObjectObject Recognition	CodeCode Available	5
Parsing Natural Scenes and Natural Language with Recursive Neural Networks	Jun 1, 2011	General ClassificationScene Classification	CodeCode Available	5
Panoramic Depth Estimation via Supervised and Unsupervised Learning in Indoor Scenes	Aug 18, 2021	Camera CalibrationDepth Estimation	CodeCode Available	5
PanoRecon: Real-Time Panoptic 3D Reconstruction from Monocular Video	Jan 1, 2024	3D Panoptic Segmentation3D Reconstruction	CodeCode Available	5
OVeNet: Offset Vector Network for Semantic Segmentation	Mar 25, 2023	Optical Character Recognition (OCR)Scene Understanding	CodeCode Available	5
OVGaussian: Generalizable 3D Gaussian Segmentation with Open Vocabularies	Dec 31, 2024	3DGS3D Semantic Segmentation	CodeCode Available	5
OST-Bench: Evaluating the Capabilities of MLLMs in Online Spatio-temporal Scene Understanding	Jul 10, 2025	Scene UnderstandingSpatial Reasoning	CodeCode Available	5
P2AT: Pyramid Pooling Axial Transformer for Real-time Semantic Segmentation	Oct 23, 2023	Autonomous DrivingDecoder	CodeCode Available	5
Parallel Neural Computing for Scene Understanding from LiDAR Perception in Autonomous Racing	Dec 24, 2024	Autonomous DrivingAutonomous Racing	CodeCode Available	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