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 1061–1070 of 1723 papers

Title	Date	Tasks	Status	Hype
3D Scene Understanding at Urban Intersection using Stereo Vision and Digital Map	Dec 10, 2021	Autonomous VehiclesNavigate	—Unverified	0
Roominoes: Generating Novel 3D Floor Plans From Existing 3D Rooms	Dec 10, 2021	3D ReconstructionAutonomous Navigation	—Unverified	0
4DContrast: Contrastive Learning with Dynamic Correspondences for 3D Scene Understanding	Dec 6, 2021	3D Instance Segmentation3D Semantic Segmentation	—Unverified	0
PolyphonicFormer: Unified Query Learning for Depth-aware Video Panoptic Segmentation	Dec 5, 2021	Depth-aware Video Panoptic SegmentationDepth Estimation	CodeCode Available	1
Behind the Curtain: Learning Occluded Shapes for 3D Object Detection	Dec 4, 2021	3D Object DetectionObject	CodeCode Available	1
Contrastive Instance Association for 4D Panoptic Segmentation using Sequences of 3D LiDAR Scans	Dec 1, 2021	4D Panoptic SegmentationAutonomous Navigation	CodeCode Available	0
Both Style and Fog Matter: Cumulative Domain Adaptation for Semantic Foggy Scene Understanding	Dec 1, 2021	DisentanglementDomain Adaptation	—Unverified	0
REMIPS: Physically Consistent 3D Reconstruction of Multiple Interacting People under Weak Supervision	Dec 1, 2021	3D Human Reconstruction3D Reconstruction	—Unverified	0
Joint Modeling of Visual Objects and Relations for Scene Graph Generation	Dec 1, 2021	Graph EmbeddingGraph Generation	—Unverified	0
AirObject: A Temporally Evolving Graph Embedding for Object Identification	Nov 30, 2021	Graph AttentionGraph Embedding	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