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	Score
LLM-Empowered Embodied Agent for Memory-Augmented Task Planning in Household Robotics	Apr 30, 2025	In-Context LearningObject	CodeCode Available	1	5
Deep Learning for Event-based Vision: A Comprehensive Survey and Benchmarks	Feb 17, 2023	DeblurringDeep Learning	CodeCode Available	1	5
A Survey on Deep Learning Technique for Video Segmentation	Jul 2, 2021	Autonomous DrivingDeep Learning	CodeCode Available	1	5
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	5
4D Panoptic LiDAR Segmentation	Feb 24, 2021	4D Panoptic SegmentationBenchmarking	CodeCode Available	1	5
Deep learning for radar data exploitation of autonomous vehicle	Mar 15, 2022	Autonomous DrivingDeep Learning	CodeCode Available	1	5
Learning Triadic Belief Dynamics in Nonverbal Communication from Videos	Apr 7, 2021	Scene Understanding	CodeCode Available	1	5
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	5
A Survey on Deep Learning for Localization and Mapping: Towards the Age of Spatial Machine Intelligence	Jun 22, 2020	Deep LearningScene Understanding	CodeCode Available	1	5
LiON: Learning Point-wise Abstaining Penalty for LiDAR Outlier DetectioN Using Diverse Synthetic Data	Sep 19, 2023	Anomaly DetectionAutonomous Driving	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