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 281–290 of 1723 papers

Title	Date	Tasks	Status	Hype
Sim-to-Real via Sim-to-Seg: End-to-end Off-road Autonomous Driving Without Real Data	Oct 25, 2022	Autonomous DrivingGPU	CodeCode Available	1
Pareto Manifold Learning: Tackling multiple tasks via ensembles of single-task models	Oct 18, 2022	image-classificationImage Classification	CodeCode Available	1
SQA3D: Situated Question Answering in 3D Scenes	Oct 14, 2022	Question AnsweringReferring Expression	CodeCode Available	1
Image Masking for Robust Self-Supervised Monocular Depth Estimation	Oct 5, 2022	Autonomous DrivingDepth Estimation	CodeCode Available	1
FreDSNet: Joint Monocular Depth and Semantic Segmentation with Fast Fourier Convolutions	Oct 4, 2022	Depth EstimationMonocular Depth Estimation	CodeCode Available	1
Uncertainty-Driven Active Vision for Implicit Scene Reconstruction	Oct 3, 2022	Scene Understanding	CodeCode Available	1
Dynamic Graph Message Passing Networks for Visual Recognition	Sep 20, 2022	image-classificationImage Classification	CodeCode Available	1
Segmenting Known Objects and Unseen Unknowns without Prior Knowledge	Sep 12, 2022	Instance SegmentationObject Detection	CodeCode Available	1
Leveraging Large (Visual) Language Models for Robot 3D Scene Understanding	Sep 12, 2022	Common Sense ReasoningScene Classification	CodeCode Available	1
MassMIND: Massachusetts Maritime INfrared Dataset	Sep 9, 2022	Instance SegmentationScene Understanding	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