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 161–170 of 1723 papers

Title	Date	Tasks	Status	Hype	Score
FreDSNet: Joint Monocular Depth and Semantic Segmentation with Fast Fourier Convolutions	Oct 4, 2022	Depth EstimationMonocular Depth Estimation	CodeCode Available	1	5
From General to Specific: Informative Scene Graph Generation via Balance Adjustment	Aug 30, 2021	BlockingGraph Generation	CodeCode Available	1	5
FloodNet: A High Resolution Aerial Imagery Dataset for Post Flood Scene Understanding	Dec 5, 2020	image-classificationImage Classification	CodeCode Available	1	5
Cross-Modal and Uncertainty-Aware Agglomeration for Open-Vocabulary 3D Scene Understanding	Mar 20, 2025	Scene Understanding	CodeCode Available	1	5
FocusFlow: Boosting Key-Points Optical Flow Estimation for Autonomous Driving	Aug 14, 2023	Autonomous DrivingOptical Flow Estimation	CodeCode Available	1	5
Context Prior for Scene Segmentation	Apr 3, 2020	Scene SegmentationScene Understanding	CodeCode Available	1	5
3DP3: 3D Scene Perception via Probabilistic Programming	Oct 30, 2021	ObjectPose Estimation	CodeCode Available	1	5
CoPeD-Advancing Multi-Robot Collaborative Perception: A Comprehensive Dataset in Real-World Environments	May 23, 2024	Pose EstimationScene Understanding	CodeCode Available	1	5
FPS-Net: A Convolutional Fusion Network for Large-Scale LiDAR Point Cloud Segmentation	Mar 1, 2021	3D Semantic SegmentationDecoder	CodeCode Available	1	5
From Multi-View to Hollow-3D: Hallucinated Hollow-3D R-CNN for 3D Object Detection	Jul 30, 2021	3D Object Detectionobject-detection	CodeCode Available	1	5

Show:10 25 50

← PrevPage 17 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