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

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Showing 1581–1590 of 1723 papers

Title	Date	Tasks	Status
Gated Driver Attention Predictor	Aug 1, 2023	Driver Attention MonitoringPrediction	CodeCode Available
A Critical Assessment of Visual Sound Source Localization Models Including Negative Audio	Oct 1, 2024	Scene UnderstandingSound Source Localization	CodeCode Available
Model-based inexact graph matching on top of CNNs for semantic scene understanding	Jan 18, 2023	Brain SegmentationDeep Learning	CodeCode Available
Gated2Depth: Real-time Dense Lidar from Gated Images	Feb 13, 2019	Scene Understanding	CodeCode Available
GaIA: Graphical Information Gain based Attention Network for Weakly Supervised Point Cloud Semantic Segmentation	Oct 2, 2022	Scene UnderstandingSegmentation	CodeCode Available
MLM: A Benchmark Dataset for Multitask Learning with Multiple Languages and Modalities	Aug 14, 2020	Representation LearningScene Understanding	CodeCode Available
FunnyNet-W: Multimodal Learning of Funny Moments in Videos in the Wild	Jan 8, 2024	Language ModellingLarge Language Model	CodeCode Available
Rotation Invariant Convolutions for 3D Point Clouds Deep Learning	Aug 17, 2019	Deep LearningScene Understanding	CodeCode Available
MLLM-SUL: Multimodal Large Language Model for Semantic Scene Understanding and Localization in Traffic Scenarios	Dec 27, 2024	Autonomous DrivingLanguage Modeling	CodeCode Available
Mitigating Object Dependencies: Improving Point Cloud Self-Supervised Learning through Object Exchange	Apr 11, 2024	ObjectScene Understanding	CodeCode Available

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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