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 591–600 of 1723 papers

Title	Date	Tasks	Status	Score
Deep Learning based Switching Filter for Impulsive Noise Removal in Color Images	Dec 3, 2019	DenoisingImage Denoising	CodeCode Available	5
BACS: Background Aware Continual Semantic Segmentation	Apr 19, 2024	Autonomous DrivingContinual Learning	CodeCode Available	5
Deep Learning--Based Scene Simplification for Bionic Vision	Jan 30, 2021	Deep LearningDepth Estimation	CodeCode Available	5
DeepIPCv2: LiDAR-powered Robust Environmental Perception and Navigational Control for Autonomous Vehicle	Jul 13, 2023	Autonomous DrivingScene Understanding	CodeCode Available	5
AVS-Net: Point Sampling with Adaptive Voxel Size for 3D Scene Understanding	Feb 27, 2024	3D Object Detection3D Part Segmentation	CodeCode Available	5
Multi-Resolution Multi-Modal Sensor Fusion For Remote Sensing Data With Label Uncertainty	May 2, 2018	Scene UnderstandingSensor Fusion	CodeCode Available	5
Multi-task Geometric Estimation of Depth and Surface Normal from Monocular 360° Images	Nov 4, 2024	Multi-Task LearningScene Understanding	CodeCode Available	5
Deep Depth from Defocus: how can defocus blur improve 3D estimation using dense neural networks?	Sep 5, 2018	3D ReconstructionDepth Estimation	CodeCode Available	5
AVQACL: A Novel Benchmark for Audio-Visual Question Answering Continual Learning	Jan 1, 2025	Audio-visual Question AnsweringContinual Learning	CodeCode Available	5
Multimodal Scale Consistency and Awareness for Monocular Self-Supervised Depth Estimation	Mar 3, 2021	Autonomous DrivingDepth Estimation	CodeCode Available	5

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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