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 761–770 of 1723 papers

Title	Date	Tasks	Status	Hype
Artifacts Mapping: Multi-Modal Semantic Mapping for Object Detection and 3D Localization	Jul 3, 2023	object-detectionObject Detection	—Unverified	0
Towards Open Vocabulary Learning: A Survey	Jun 28, 2023	Open Set LearningOut-of-Distribution Detection	CodeCode Available	2
Generalizing Surgical Instruments Segmentation to Unseen Domains with One-to-Many Synthesis	Jun 28, 2023	Scene Understanding	CodeCode Available	0
Style-transfer based Speech and Audio-visual Scene Understanding for Robot Action Sequence Acquisition from Videos	Jun 27, 2023	Multi-Task LearningScene Understanding	—Unverified	0
SSC-RS: Elevate LiDAR Semantic Scene Completion with Representation Separation and BEV Fusion	Jun 27, 2023	Autonomous DrivingScene Understanding	CodeCode Available	1
Physion++: Evaluating Physical Scene Understanding that Requires Online Inference of Different Physical Properties	Jun 27, 2023	FrictionScene Understanding	—Unverified	0
Towards Unseen Triples: Effective Text-Image-joint Learning for Scene Graph Generation	Jun 23, 2023	Graph GenerationScene Graph Generation	—Unverified	0
Semantic-aware Transmission for Robust Point Cloud Classification	Jun 23, 2023	ClassificationDecoder	—Unverified	0
OpenMask3D: Open-Vocabulary 3D Instance Segmentation	Jun 23, 2023	3D Instance Segmentation3D Open-Vocabulary Instance Segmentation	CodeCode Available	2
Multi-view 3D Object Reconstruction and Uncertainty Modelling with Neural Shape Prior	Jun 17, 2023	3D Object ReconstructionObject	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