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 211–220 of 1723 papers

Title	Date	Tasks	Status	Hype
TPSeNCE: Towards Artifact-Free Realistic Rain Generation for Deraining and Object Detection in Rain	Nov 1, 2023	Contrastive LearningImage-to-Image Translation	CodeCode Available	1
TransRadar: Adaptive-Directional Transformer for Real-Time Multi-View Radar Semantic Segmentation	Oct 3, 2023	Autonomous DrivingScene Understanding	CodeCode Available	1
Talk2BEV: Language-enhanced Bird's-eye View Maps for Autonomous Driving	Oct 3, 2023	Autonomous DrivingDecision Making	CodeCode Available	1
Multimodal Dataset for Localization, Mapping and Crop Monitoring in Citrus Tree Farms	Sep 27, 2023	object-detectionObject Detection	CodeCode Available	1
PanopticNDT: Efficient and Robust Panoptic Mapping	Sep 24, 2023	2D Panoptic Segmentation3D Panoptic Segmentation	CodeCode Available	1
LiON: Learning Point-wise Abstaining Penalty for LiDAR Outlier DetectioN Using Diverse Synthetic Data	Sep 19, 2023	Anomaly DetectionAutonomous Driving	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
HOC-Search: Efficient CAD Model and Pose Retrieval from RGB-D Scans	Sep 12, 2023	3D Object Retrieval3D Scene Reconstruction	CodeCode Available	1
Multi3DRefer: Grounding Text Description to Multiple 3D Objects	Sep 11, 2023	3D visual groundingContrastive Learning	CodeCode Available	1
Vote2Cap-DETR++: Decoupling Localization and Describing for End-to-End 3D Dense Captioning	Sep 6, 2023	3D dense captioningCaption Generation	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