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
DD-PPO: Learning Near-Perfect PointGoal Navigators from 2.5 Billion Frames	Nov 1, 2019	Autonomous NavigationGPU	CodeCode Available	1
LWSIS: LiDAR-guided Weakly Supervised Instance Segmentation for Autonomous Driving	Dec 7, 2022	Autonomous DrivingInstance Segmentation	CodeCode Available	1
Masked Scene Modeling: Narrowing the Gap Between Supervised and Self-Supervised Learning in 3D Scene Understanding	Apr 9, 2025	Scene UnderstandingSelf-Supervised Learning	CodeCode Available	1
MassMIND: Massachusetts Maritime INfrared Dataset	Sep 9, 2022	Instance SegmentationScene Understanding	CodeCode Available	1
AVSegFormer: Audio-Visual Segmentation with Transformer	Jul 3, 2023	DecoderScene Understanding	CodeCode Available	1
MGNet: Monocular Geometric Scene Understanding for Autonomous Driving	Jun 27, 2022	Autonomous DrivingDepth Estimation	CodeCode Available	1
A2-FPN for Semantic Segmentation of Fine-Resolution Remotely Sensed Images	Feb 16, 2021	Decision MakingScene Understanding	CodeCode Available	1
AeroRIT: A New Scene for Hyperspectral Image Analysis	Dec 17, 2019	Hyperspectral image analysisImage Super-Resolution	CodeCode Available	1
A Versatile and Efficient Reinforcement Learning Framework for Autonomous Driving	Oct 22, 2021	Autonomous Drivingreinforcement-learning	CodeCode Available	1
FPS-Net: A Convolutional Fusion Network for Large-Scale LiDAR Point Cloud Segmentation	Mar 1, 2021	3D Semantic SegmentationDecoder	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