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 681–690 of 1723 papers

Title	Date	Tasks	Status	Hype
Single-view 3D Scene Reconstruction with High-fidelity Shape and Texture	Nov 1, 2023	3D Object Reconstruction3D Reconstruction	—Unverified	0
Recent Advances in Multi-modal 3D Scene Understanding: A Comprehensive Survey and Evaluation	Oct 24, 2023	Autonomous DrivingScene Understanding	—Unverified	0
P2AT: Pyramid Pooling Axial Transformer for Real-time Semantic Segmentation	Oct 23, 2023	Autonomous DrivingDecoder	CodeCode Available	0
Panoptic Out-of-Distribution Segmentation	Oct 18, 2023	Data AugmentationInstance Segmentation	—Unverified	0
S4C: Self-Supervised Semantic Scene Completion with Neural Fields	Oct 11, 2023	Image SegmentationNavigate	—Unverified	0
DualMLP: a two-stream fusion model for 3D point cloud classification	Oct 10, 2023	3D Point Cloud ClassificationPoint Cloud Classification	CodeCode Available	0
Zero-Shot Open-Vocabulary Tracking with Large Pre-Trained Models	Oct 10, 2023	ObjectObject Tracking	—Unverified	0
TextPSG: Panoptic Scene Graph Generation from Textual Descriptions	Oct 10, 2023	Graph GenerationPanoptic Scene Graph Generation	—Unverified	0
Talk2BEV: Language-enhanced Bird's-eye View Maps for Autonomous Driving	Oct 3, 2023	Autonomous DrivingDecision Making	CodeCode Available	1
TransRadar: Adaptive-Directional Transformer for Real-Time Multi-View Radar Semantic Segmentation	Oct 3, 2023	Autonomous DrivingScene Understanding	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