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 321–330 of 1723 papers

Title	Date	Tasks	Status	Hype
SafePicking: Learning Safe Object Extraction via Object-Level Mapping	Feb 11, 2022	Motion PlanningObject	CodeCode Available	1
Transformers in Self-Supervised Monocular Depth Estimation with Unknown Camera Intrinsics	Feb 7, 2022	Autonomous DrivingDepth Estimation	CodeCode Available	1
Global-Reasoned Multi-Task Learning Model for Surgical Scene Understanding	Jan 28, 2022	Graph AttentionKnowledge Distillation	CodeCode Available	1
MonoDistill: Learning Spatial Features for Monocular 3D Object Detection	Jan 26, 2022	3D Object DetectionMonocular 3D Object Detection	CodeCode Available	1
Point Cloud Pre-Training With Natural 3D Structures	Jan 1, 2022	3D Object Detectionobject-detection	CodeCode Available	1
MSeg: A Composite Dataset for Multi-domain Semantic Segmentation	Dec 27, 2021	Computational EfficiencyInstance Segmentation	CodeCode Available	1
Channel-Wise Attention-Based Network for Self-Supervised Monocular Depth Estimation	Dec 24, 2021	Depth EstimationDepth Prediction	CodeCode Available	1
Comprehensive Visual Question Answering on Point Clouds through Compositional Scene Manipulation	Dec 22, 2021	Common Sense ReasoningQuestion Answering	CodeCode Available	1
ScanQA: 3D Question Answering for Spatial Scene Understanding	Dec 20, 2021	3D Question Answering (3D-QA)Object	CodeCode Available	1
Activation Modulation and Recalibration Scheme for Weakly Supervised Semantic Segmentation	Dec 16, 2021	Feature ImportanceScene Understanding	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