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

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Showing 231–240 of 1723 papers

Title	Date	Tasks	Status	Hype
Expressive Scene Graph Generation Using Commonsense Knowledge Infusion for Visual Understanding and Reasoning	May 31, 2022	Common Sense ReasoningGraph Generation	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
LWSIS: LiDAR-guided Weakly Supervised Instance Segmentation for Autonomous Driving	Dec 7, 2022	Autonomous DrivingInstance Segmentation	CodeCode Available	1
Campus3D: A Photogrammetry Point Cloud Benchmark for Hierarchical Understanding of Outdoor Scene	Aug 11, 2020	Instance SegmentationPoint Cloud Segmentation	CodeCode Available	1
Mask4D: End-to-End Mask-Based 4D Panoptic Segmentation for LiDAR Sequences	Sep 18, 2023	3D Panoptic Segmentation4D Panoptic 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
MCTS with Refinement for Proposals Selection Games in Scene Understanding	Jul 7, 2022	Scene Understanding	CodeCode Available	1
MGNet: Monocular Geometric Scene Understanding for Autonomous Driving	Jun 27, 2022	Autonomous DrivingDepth Estimation	CodeCode Available	1
All-Day Multi-Camera Multi-Target Tracking	Jan 1, 2025	AllMamba	CodeCode Available	1
Enhancing Scene Graph Generation with Hierarchical Relationships and Commonsense Knowledge	Nov 21, 2023	Large Language ModelMultimodal Deep Learning	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