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 881–890 of 1723 papers

Title	Date	Tasks	Status	Hype
Self-Supervised Object Detection from Egocentric Videos	Jan 1, 2023	Class-agnostic Object DetectionObject	—Unverified	0
Uni-3D: A Universal Model for Panoptic 3D Scene Reconstruction	Jan 1, 2023	3D Scene ReconstructionImage Segmentation	CodeCode Available	1
Seeing With Sound: Long-range Acoustic Beamforming for Multimodal Scene Understanding	Jan 1, 2023	Autonomous Vehiclesobject-detection	—Unverified	0
Learning Geometric-Aware Properties in 2D Representation Using Lightweight CAD Models, or Zero Real 3D Pairs	Jan 1, 2023	Scene Understanding	—Unverified	0
Combining Implicit-Explicit View Correlation for Light Field Semantic Segmentation	Jan 1, 2023	Scene UnderstandingSegmentation	—Unverified	0
PeakConv: Learning Peak Receptive Field for Radar Semantic Segmentation	Jan 1, 2023	ObjectScene Understanding	CodeCode Available	1
Attentional Graph Convolutional Network for Structure-aware Audio-Visual Scene Classification	Dec 31, 2022	Scene ClassificationScene Recognition	—Unverified	0
PointVST: Self-Supervised Pre-training for 3D Point Clouds via View-Specific Point-to-Image Translation	Dec 29, 2022	Contrastive LearningImage Generation	CodeCode Available	1
Confidence-Aware Paced-Curriculum Learning by Label Smoothing for Surgical Scene Understanding	Dec 22, 2022	Multi-Label ClassificationMUlTI-LABEL-ClASSIFICATION	CodeCode Available	0
METEOR Guided Divergence for Video Captioning	Dec 20, 2022	Hierarchical Reinforcement LearningScene Understanding	CodeCode Available	0

Show:10 25 50

← PrevPage 89 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