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 401–410 of 1723 papers

Title	Date	Tasks	Status	Hype
Distilled Semantics for Comprehensive Scene Understanding from Videos	Mar 31, 2020	Depth EstimationKnowledge Distillation	CodeCode Available	1
Pre-trained Text-to-Image Diffusion Models Are Versatile Representation Learners for Control	May 9, 2024	Representation LearningScene Understanding	CodeCode Available	1
Exploring Data-Efficient 3D Scene Understanding with Contrastive Scene Contexts	Dec 16, 2020	3D Semantic SegmentationInstance Segmentation	CodeCode Available	1
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
PyTorchGeoNodes: Enabling Differentiable Shape Programs for 3D Shape Reconstruction	Apr 16, 2024	3D Reconstruction3D Shape Reconstruction	CodeCode Available	1
RADIATE: A Radar Dataset for Automotive Perception in Bad Weather	Oct 18, 2020	Autonomous DrivingBenchmarking	CodeCode Available	1
Estimating Generic 3D Room Structures from 2D Annotations	Jun 15, 2023	Scene Understanding	CodeCode Available	1
Cityscapes-Panoptic-Parts and PASCAL-Panoptic-Parts datasets for Scene Understanding	Apr 16, 2020	Human Part SegmentationPanoptic Segmentation	CodeCode Available	1
Event-aided Semantic Scene Completion	Feb 4, 2025	Autonomous DrivingScene Understanding	CodeCode Available	1
Egocentric Scene Understanding via Multimodal Spatial Rectifier	Jul 14, 2022	Scene UnderstandingSurface Normal Estimation	CodeCode Available	1

Show:10 25 50

← PrevPage 41 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