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 91–100 of 1723 papers

Title	Date	Tasks	Status	Hype
TaskExpert: Dynamically Assembling Multi-Task Representations with Memorial Mixture-of-Experts	Jul 28, 2023	Long-range modelingMixture-of-Experts	CodeCode Available	2
A Survey on Open-Vocabulary Detection and Segmentation: Past, Present, and Future	Jul 18, 2023	Knowledge Distillationobject-detection	CodeCode Available	2
Towards Open Vocabulary Learning: A Survey	Jun 28, 2023	Open Set LearningOut-of-Distribution Detection	CodeCode Available	2
OpenMask3D: Open-Vocabulary 3D Instance Segmentation	Jun 23, 2023	3D Instance Segmentation3D Open-Vocabulary Instance Segmentation	CodeCode Available	2
InvPT++: Inverted Pyramid Multi-Task Transformer for Visual Scene Understanding	Jun 8, 2023	DecoderMulti-Task Learning	CodeCode Available	2
TextSLAM: Visual SLAM with Semantic Planar Text Features	May 17, 2023	Mixed RealityObject SLAM	CodeCode Available	2
TaskPrompter: Spatial-Channel Multi-Task Prompting for Dense Scene Understanding	May 1, 2023	3D Object DetectionMonocular Depth Estimation	CodeCode Available	2
Swin3D: A Pretrained Transformer Backbone for 3D Indoor Scene Understanding	Apr 14, 2023	3D Object DetectionScene Understanding	CodeCode Available	2
Graph-based Topology Reasoning for Driving Scenes	Apr 11, 2023	3D Lane DetectionAutonomous Driving	CodeCode Available	2
RegionPLC: Regional Point-Language Contrastive Learning for Open-World 3D Scene Understanding	Apr 3, 2023	Contrastive LearningInstance Segmentation	CodeCode Available	2

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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