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 821–830 of 1723 papers

Title	Date	Tasks	Status	Hype
Learning How To Robustly Estimate Camera Pose in Endoscopic Videos	Apr 17, 2023	3D ReconstructionCamera Pose Estimation	CodeCode Available	1
STRAP: Structured Object Affordance Segmentation with Point Supervision	Apr 17, 2023	ObjectScene Understanding	CodeCode Available	1
Swin3D: A Pretrained Transformer Backbone for 3D Indoor Scene Understanding	Apr 14, 2023	3D Object DetectionScene Understanding	CodeCode Available	2
iDisc: Internal Discretization for Monocular Depth Estimation	Apr 13, 2023	Autonomous DrivingDepth Estimation	CodeCode Available	3
Graph-based Topology Reasoning for Driving Scenes	Apr 11, 2023	3D Lane DetectionAutonomous Driving	CodeCode Available	2
Semantic Segmentation with High Inference Speed in Off-Road Environments	Apr 10, 2023	2D Semantic SegmentationAutonomous Vehicles	CodeCode Available	0
Video-kMaX: A Simple Unified Approach for Online and Near-Online Video Panoptic Segmentation	Apr 10, 2023	Panoptic SegmentationScene Understanding	—Unverified	0
FREDOM: Fairness Domain Adaptation Approach to Semantic Scene Understanding	Apr 4, 2023	Autonomous DrivingDomain Adaptation	CodeCode Available	0
RegionPLC: Regional Point-Language Contrastive Learning for Open-World 3D Scene Understanding	Apr 3, 2023	Contrastive LearningInstance Segmentation	CodeCode Available	2
Object-agnostic Affordance Categorization via Unsupervised Learning of Graph Embeddings	Mar 30, 2023	ObjectScene Understanding	—Unverified	0

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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