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 751–760 of 1723 papers

Title	Date	Tasks	Status	Hype
Open Scene Understanding: Grounded Situation Recognition Meets Segment Anything for Helping People with Visual Impairments	Jul 15, 2023	DecoderGrounded Situation Recognition	CodeCode Available	1
DeepIPCv2: LiDAR-powered Robust Environmental Perception and Navigational Control for Autonomous Vehicle	Jul 13, 2023	Autonomous DrivingScene Understanding	CodeCode Available	0
Smart Infrastructure: A Research Junction	Jul 12, 2023	Scene UnderstandingSynthetic Data Generation	—Unverified	0
The IMPTC Dataset: An Infrastructural Multi-Person Trajectory and Context Dataset	Jul 12, 2023	Scene Understanding	CodeCode Available	1
CAT-ViL: Co-Attention Gated Vision-Language Embedding for Visual Question Localized-Answering in Robotic Surgery	Jul 11, 2023	Question AnsweringScene Understanding	CodeCode Available	1
Test-Time Adaptation for Nighttime Color-Thermal Semantic Segmentation	Jul 10, 2023	Scene UnderstandingSemantic Segmentation	—Unverified	0
PSDR-Room: Single Photo to Scene using Differentiable Rendering	Jul 6, 2023	Scene Understanding	—Unverified	0
Towards accurate instance segmentation in large-scale LiDAR point clouds	Jul 6, 2023	ClusteringInstance Segmentation	CodeCode Available	1
Object Recognition System on a Tactile Device for Visually Impaired	Jul 5, 2023	object-detectionObject Detection	—Unverified	0
AVSegFormer: Audio-Visual Segmentation with Transformer	Jul 3, 2023	DecoderScene 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