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 1001–1010 of 1723 papers

Title	Date	Tasks	Status	Hype
MTANet: Multitask-Aware Network With Hierarchical Multimodal Fusion for RGB-T Urban Scene Understanding	Apr 5, 2022	Autonomous VehiclesScene Understanding	—Unverified	0
P3Depth: Monocular Depth Estimation with a Piecewise Planarity Prior	Apr 5, 2022	Depth EstimationMonocular Depth Estimation	CodeCode Available	1
BinsFormer: Revisiting Adaptive Bins for Monocular Depth Estimation	Apr 3, 2022	DecoderDepth Estimation	CodeCode Available	2
Online panoptic 3D reconstruction as a Linear Assignment Problem	Apr 1, 2022	3D ReconstructionImage Segmentation	CodeCode Available	1
Point Scene Understanding via Disentangled Instance Mesh Reconstruction	Mar 31, 2022	RetrievalScene Understanding	CodeCode Available	1
Collaborative Transformers for Grounded Situation Recognition	Mar 30, 2022	Grounded Situation RecognitionImage Classification	CodeCode Available	1
Multi-Task Learning for Visual Scene Understanding	Mar 28, 2022	Multi-Task LearningScene Understanding	—Unverified	0
Learning to Answer Questions in Dynamic Audio-Visual Scenarios	Mar 26, 2022	audio-visual learningAudio-visual Question Answering	CodeCode Available	1
Semi-supervised and Deep learning Frameworks for Video Classification and Key-frame Identification	Mar 25, 2022	RetrievalScene Understanding	—Unverified	0
Towards Escaping from Language Bias and OCR Error: Semantics-Centered Text Visual Question Answering	Mar 24, 2022	Optical Character RecognitionOptical Character Recognition (OCR)	—Unverified	0

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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