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 341–350 of 1723 papers

Title	Date	Tasks	Status	Hype	Score
DD-PPO: Learning Near-Perfect PointGoal Navigators from 2.5 Billion Frames	Nov 1, 2019	Autonomous NavigationGPU	CodeCode Available	1	5
AeroRIT: A New Scene for Hyperspectral Image Analysis	Dec 17, 2019	Hyperspectral image analysisImage Super-Resolution	CodeCode Available	1	5
GFF: Gated Fully Fusion for Semantic Segmentation	Apr 3, 2019	Scene ParsingScene Understanding	CodeCode Available	1	5
DI-V2X: Learning Domain-Invariant Representation for Vehicle-Infrastructure Collaborative 3D Object Detection	Dec 25, 2023	3D Object Detectionobject-detection	CodeCode Available	1	5
MonteBoxFinder: Detecting and Filtering Primitives to Fit a Noisy Point Cloud	Jul 28, 2022	Scene Understanding	CodeCode Available	1	5
Global Aggregation then Local Distribution in Fully Convolutional Networks	Sep 16, 2019	Instance Segmentationobject-detection	CodeCode Available	1	5
Digging Into Self-Supervised Monocular Depth Estimation	Jun 4, 2018	Camera Pose EstimationDepth Estimation	CodeCode Available	1	5
DTCLMapper: Dual Temporal Consistent Learning for Vectorized HD Map Construction	May 9, 2024	Contrastive LearningScene Understanding	CodeCode Available	1	5
GOV-NeSF: Generalizable Open-Vocabulary Neural Semantic Fields	Apr 1, 2024	Open Vocabulary Semantic SegmentationOpen-Vocabulary Semantic Segmentation	CodeCode Available	1	5
CLIP2Scene: Towards Label-efficient 3D Scene Understanding by CLIP	Jan 12, 2023	3D Semantic SegmentationContrastive Learning	CodeCode Available	1	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