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 1561–1570 of 1723 papers

Title	Date	Tasks	Status
ResUNet-a: a deep learning framework for semantic segmentation of remotely sensed data	Apr 1, 2019	Scene ParsingScene Understanding	CodeCode Available
Hierarchical Superpixel Segmentation via Structural Information Theory	Jan 13, 2025	graph constructiongraph partitioning	CodeCode Available
Hierarchical Spatial Proximity Reasoning for Vision-and-Language Navigation	Mar 18, 2024	Common Sense ReasoningEfficient Exploration	CodeCode Available
Veritatem Dies Aperit- Temporally Consistent Depth Prediction Enabled by a Multi-Task Geometric and Semantic Scene Understanding Approach	Mar 26, 2019	Autonomous DrivingDepth Completion	CodeCode Available
Veritatem Dies Aperit - Temporally Consistent Depth Prediction Enabled by a Multi-Task Geometric and Semantic Scene Understanding Approach	Jun 1, 2019	Autonomous DrivingDepth Completion	CodeCode Available
Hierarchical Context Transformer for Multi-level Semantic Scene Understanding	Feb 21, 2025	Contrastive LearningRepresentation Learning	CodeCode Available
Grid-augmented vision: A simple yet effective approach for enhanced spatial understanding in multi-modal agents	Nov 27, 2024	Autonomous NavigationObject Recognition	CodeCode Available
Revisiting Distillation for Continual Learning on Visual Question Localized-Answering in Robotic Surgery	Jul 22, 2023	Continual LearningScene Understanding	CodeCode Available
MultiDepth: Single-Image Depth Estimation via Multi-Task Regression and Classification	Jul 25, 2019	Autonomous VehiclesClassification	CodeCode Available
MovSAM: A Single-image Moving Object Segmentation Framework Based on Deep Thinking	Apr 9, 2025	Autonomous DrivingLanguage Modeling	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