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 931–940 of 1723 papers

Title	Date	Tasks	Status	Hype
Flow-based GAN for 3D Point Cloud Generation from a Single Image	Oct 8, 2022	Point Cloud GenerationScene Understanding	CodeCode Available	0
Feature-Realistic Neural Fusion for Real-Time, Open Set Scene Understanding	Oct 6, 2022	Scene Understanding	—Unverified	0
Image Masking for Robust Self-Supervised Monocular Depth Estimation	Oct 5, 2022	Autonomous DrivingDepth Estimation	CodeCode Available	1
FreDSNet: Joint Monocular Depth and Semantic Segmentation with Fast Fourier Convolutions	Oct 4, 2022	Depth EstimationMonocular Depth Estimation	CodeCode Available	1
Uncertainty-Driven Active Vision for Implicit Scene Reconstruction	Oct 3, 2022	Scene Understanding	CodeCode Available	1
GaIA: Graphical Information Gain based Attention Network for Weakly Supervised Point Cloud Semantic Segmentation	Oct 2, 2022	Scene UnderstandingSegmentation	CodeCode Available	0
A Survey on Knowledge Graph-based Methods for Automated Driving	Sep 30, 2022	Knowledge Graph EmbeddingsKnowledge Graphs	—Unverified	0
Towards Multimodal Multitask Scene Understanding Models for Indoor Mobile Agents	Sep 27, 2022	3D Object DetectionAutonomous Driving	—Unverified	0
Stochastic Future Prediction in Real World Driving Scenarios	Sep 21, 2022	Autonomous DrivingFuture prediction	—Unverified	0
Dynamic Graph Message Passing Networks for Visual Recognition	Sep 20, 2022	image-classificationImage Classification	CodeCode Available	1

Show:10 25 50

← PrevPage 94 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