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 611–620 of 1723 papers

Title	Date	Tasks	Status	Score
Cross-Modality Time-Variant Relation Learning for Generating Dynamic Scene Graphs	May 15, 2023	RelationScene Graph Generation	CodeCode Available	5
CrossModalityDiffusion: Multi-Modal Novel View Synthesis with Unified Intermediate Representation	Jan 16, 2025	Novel View SynthesisScene Understanding	CodeCode Available	5
Multimodal Scale Consistency and Awareness for Monocular Self-Supervised Depth Estimation	Mar 3, 2021	Autonomous DrivingDepth Estimation	CodeCode Available	5
Auto-Embedding Generative Adversarial Networks for High Resolution Image Synthesis	Mar 27, 2019	Generative Adversarial NetworkImage Generation	CodeCode Available	5
MovSAM: A Single-image Moving Object Segmentation Framework Based on Deep Thinking	Apr 9, 2025	Autonomous DrivingLanguage Modeling	CodeCode Available	5
MonoGRNet: A Geometric Reasoning Network for Monocular 3D Object Localization	Nov 26, 2018	2D Object Detection3D Object Detection	CodeCode Available	5
Cooperative Holistic Scene Understanding: Unifying 3D Object, Layout, and Camera Pose Estimation	Oct 31, 2018	3D Object DetectionCamera Pose Estimation	CodeCode Available	5
Contrastive Instance Association for 4D Panoptic Segmentation using Sequences of 3D LiDAR Scans	Dec 1, 2021	4D Panoptic SegmentationAutonomous Navigation	CodeCode Available	5
Continual Learning of Unsupervised Monocular Depth from Videos	Nov 4, 2023	Autonomous DrivingContinual Learning	CodeCode Available	5
Modeling Expectation Violation in Intuitive Physics with Coarse Probabilistic Object Representations	Dec 1, 2019	Scene Understanding	CodeCode Available	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