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 331–340 of 1723 papers

Title	Date	Tasks	Status	Hype
All-Day Multi-Camera Multi-Target Tracking	Jan 1, 2025	AllMamba	CodeCode Available	1
Learning to Tune Like an Expert: Interpretable and Scene-Aware Navigation via MLLM Reasoning and CVAE-Based Adaptation	Jul 15, 2025	Large Language ModelScene Understanding	CodeCode Available	1
A2-FPN for Semantic Segmentation of Fine-Resolution Remotely Sensed Images	Feb 16, 2021	Decision MakingScene Understanding	CodeCode Available	1
DAF-Net: A Dual-Branch Feature Decomposition Fusion Network with Domain Adaptive for Infrared and Visible Image Fusion	Sep 18, 2024	Infrared And Visible Image FusionScene Understanding	CodeCode Available	1
Exploiting Edge-Oriented Reasoning for 3D Point-based Scene Graph Analysis	Mar 9, 2021	3d scene graph generationgraph construction	CodeCode Available	1
Dense Audio-Visual Event Localization under Cross-Modal Consistency and Multi-Temporal Granularity Collaboration	Dec 17, 2024	audio-visual event localizationaudio-visual learning	CodeCode Available	1
Light Field Networks: Neural Scene Representations with Single-Evaluation Rendering	Jun 4, 2021	Meta-LearningScene Understanding	CodeCode Available	1
LinkNet: Exploiting Encoder Representations for Efficient Semantic Segmentation	Jun 14, 2017	GPUScene Understanding	CodeCode Available	1
DC-SAM: In-Context Segment Anything in Images and Videos via Dual Consistency	Apr 16, 2025	Few-Shot LearningInteractive Segmentation	CodeCode Available	1
AeroRIT: A New Scene for Hyperspectral Image Analysis	Dec 17, 2019	Hyperspectral image analysisImage Super-Resolution	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