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 191–200 of 1723 papers

Title	Date	Tasks	Status	Hype	Score
Deep learning for radar data exploitation of autonomous vehicle	Mar 15, 2022	Autonomous DrivingDeep Learning	CodeCode Available	1	5
Curriculum Model Adaptation with Synthetic and Real Data for Semantic Foggy Scene Understanding	Jan 5, 2019	Domain AdaptationScene Understanding	CodeCode Available	1	5
AVSegFormer: Audio-Visual Segmentation with Transformer	Jul 3, 2023	DecoderScene Understanding	CodeCode Available	1	5
Detecting Human-Object Interaction via Fabricated Compositional Learning	Mar 15, 2021	Affordance RecognitionHuman-Object Interaction Detection	CodeCode Available	1	5
Bi-level Dynamic Learning for Jointly Multi-modality Image Fusion and Beyond	May 11, 2023	Scene Understanding	CodeCode Available	1	5
CSFNet: A Cosine Similarity Fusion Network for Real-Time RGB-X Semantic Segmentation of Driving Scenes	Jul 1, 2024	Autonomous VehiclesImage Segmentation	CodeCode Available	1	5
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	5
Diffusion-SS3D: Diffusion Model for Semi-supervised 3D Object Detection	Dec 5, 2023	3D Object DetectionDenoising	CodeCode Available	1	5
Grounded Situation Recognition with Transformers	Nov 19, 2021	DecoderGrounded Situation Recognition	CodeCode Available	1	5
Global Aggregation then Local Distribution in Fully Convolutional Networks	Sep 16, 2019	Instance Segmentationobject-detection	CodeCode Available	1	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