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 451–460 of 1723 papers

Title	Date	Tasks	Status	Hype
3UR-LLM: An End-to-End Multimodal Large Language Model for 3D Scene Understanding	Jan 14, 2025	Language ModelingLanguage Modelling	CodeCode Available	1
TextSLAM: Visual SLAM with Planar Text Features	Nov 26, 2019	Object SLAMScene Understanding	CodeCode Available	1
Channel-Wise Attention-Based Network for Self-Supervised Monocular Depth Estimation	Dec 24, 2021	Depth EstimationDepth Prediction	CodeCode Available	1
The Cityscapes Dataset for Semantic Urban Scene Understanding	Apr 6, 2016	object-detectionObject Detection	CodeCode Available	1
FloodNet: A High Resolution Aerial Imagery Dataset for Post Flood Scene Understanding	Dec 5, 2020	image-classificationImage Classification	CodeCode Available	1
CAKES: Channel-wise Automatic KErnel Shrinking for Efficient 3D Networks	Mar 28, 2020	3D Medical Imaging SegmentationAction Recognition	CodeCode Available	1
F-ViTA: Foundation Model Guided Visible to Thermal Translation	Apr 3, 2025	Scene UnderstandingStyle Transfer	CodeCode Available	1
Toronto-3D: A Large-scale Mobile LiDAR Dataset for Semantic Segmentation of Urban Roadways	Mar 18, 2020	3D Semantic SegmentationAutonomous Driving	CodeCode Available	1
Grounded Situation Recognition with Transformers	Nov 19, 2021	DecoderGrounded Situation Recognition	CodeCode Available	1
Image Masking for Robust Self-Supervised Monocular Depth Estimation	Oct 5, 2022	Autonomous DrivingDepth Estimation	CodeCode Available	1

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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