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 251–260 of 1723 papers

Title	Date	Tasks	Status	Hype
Learning How To Robustly Estimate Camera Pose in Endoscopic Videos	Apr 17, 2023	3D ReconstructionCamera Pose Estimation	CodeCode Available	1
STRAP: Structured Object Affordance Segmentation with Point Supervision	Apr 17, 2023	ObjectScene Understanding	CodeCode Available	1
ViPLO: Vision Transformer based Pose-Conditioned Self-Loop Graph for Human-Object Interaction Detection	Apr 17, 2023	Human-Object Interaction DetectionQuantization	CodeCode Available	1
RS2G: Data-Driven Scene-Graph Extraction and Embedding for Robust Autonomous Perception and Scenario Understanding	Apr 17, 2023	Autonomous VehiclesGraph Learning	CodeCode Available	1
Complementary Random Masking for RGB-Thermal Semantic Segmentation	Mar 30, 2023	Scene UnderstandingSemantic Segmentation	CodeCode Available	1
DPF: Learning Dense Prediction Fields with Weak Supervision	Mar 29, 2023	Intrinsic Image DecompositionPrediction	CodeCode Available	1
HiLo: Exploiting High Low Frequency Relations for Unbiased Panoptic Scene Graph Generation	Mar 28, 2023	Panoptic Scene Graph GenerationScene Graph Generation	CodeCode Available	1
Real-Time Semantic Segmentation using Hyperspectral Images for Mapping Unstructured and Unknown Environments	Mar 27, 2023	Autonomous NavigationReal-Time Semantic Segmentation	CodeCode Available	1
You Only Need One Thing One Click: Self-Training for Weakly Supervised 3D Scene Understanding	Mar 26, 2023	3D Instance SegmentationInstance Segmentation	CodeCode Available	1
Viewpoint Equivariance for Multi-View 3D Object Detection	Mar 25, 2023	3D Object DetectionObject	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