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 511–520 of 1723 papers

Title	Date	Tasks	Status	Score
3D Semantic Segmentation of Modular Furniture using rjMCMC	May 15, 2017	3D Semantic Segmentationfurniture segmentation	CodeCode Available	5
ResUNet-a: a deep learning framework for semantic segmentation of remotely sensed data	Apr 1, 2019	Scene ParsingScene Understanding	CodeCode Available	5
One model to use them all: Training a segmentation model with complementary datasets	Feb 29, 2024	AllAnatomy	CodeCode Available	5
SemanticKITTI: A Dataset for Semantic Scene Understanding of LiDAR Sequences	Apr 2, 2019	3D Semantic SegmentationScene Understanding	CodeCode Available	5
Omni-Recon: Harnessing Image-based Rendering for General-Purpose Neural Radiance Fields	Mar 17, 2024	3D ReconstructionNeRF	CodeCode Available	5
Bridging Stereo Matching and Optical Flow via Spatiotemporal Correspondence	May 22, 2019	Optical Flow EstimationScene Understanding	CodeCode Available	5
AP-MTL: Attention Pruned Multi-task Learning Model for Real-time Instrument Detection and Segmentation in Robot-assisted Surgery	Mar 10, 2020	Multi-Task LearningScene Understanding	CodeCode Available	5
DualMLP: a two-stream fusion model for 3D point cloud classification	Oct 10, 2023	3D Point Cloud ClassificationPoint Cloud Classification	CodeCode Available	5
Dual-Glance Model for Deciphering Social Relationships	Aug 2, 2017	modelobject-detection	CodeCode Available	5
A Plug-and-Play Method for Rare Human-Object Interactions Detection by Bridging Domain Gap	Jul 31, 2024	Human-Object Interaction DetectionImage Reconstruction	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