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 1221–1230 of 1723 papers

Title	Date	Tasks	Status	Hype
Deep Learning--Based Scene Simplification for Bionic Vision	Jan 30, 2021	Deep LearningDepth Estimation	CodeCode Available	0
OpenGF: An Ultra-Large-Scale Ground Filtering Dataset Built Upon Open ALS Point Clouds Around the World	Jan 24, 2021	3D Semantic SegmentationDeep Learning	CodeCode Available	1
The Ikshana Hypothesis of Human Scene Understanding	Jan 21, 2021	Representation LearningScene Understanding	CodeCode Available	0
Rethinking Semantic Segmentation Evaluation for Explainability and Model Selection	Jan 21, 2021	Autonomous NavigationModel Selection	—Unverified	0
SOSD-Net: Joint Semantic Object Segmentation and Depth Estimation from Monocular images	Jan 19, 2021	Depth EstimationMonocular Depth Estimation	—Unverified	0
Automatic Extrinsic Calibration Method for LiDAR and Camera Sensor Setups	Jan 12, 2021	Scene Understanding	CodeCode Available	1
Grounding Consistency: Distilling Spatial Common Sense for Precise Visual Relationship Detection	Jan 1, 2021	Common Sense ReasoningGraph Generation	CodeCode Available	1
BUTLER: Building Understanding in TextWorld via Language for Embodied Reasoning	Jan 1, 2021	Scene Understanding	—Unverified	0
Non-maximum Suppression Also Closes the Variational Approximation Gap of Multi-object Variational Autoencoders	Jan 1, 2021	ObjectRepresentation Learning	—Unverified	0
Pseudo Label-Guided Multi Task Learning for Scene Understanding	Jan 1, 2021	Depth EstimationMonocular Depth Estimation	—Unverified	0

Show:10 25 50

← PrevPage 123 of 173Next →

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