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 151–160 of 1723 papers

Title	Date	Tasks	Status	Hype	Score
CoPeD-Advancing Multi-Robot Collaborative Perception: A Comprehensive Dataset in Real-World Environments	May 23, 2024	Pose EstimationScene Understanding	CodeCode Available	1	5
FPS-Net: A Convolutional Fusion Network for Large-Scale LiDAR Point Cloud Segmentation	Mar 1, 2021	3D Semantic SegmentationDecoder	CodeCode Available	1	5
A2-FPN for Semantic Segmentation of Fine-Resolution Remotely Sensed Images	Feb 16, 2021	Decision MakingScene 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
Context Prior for Scene Segmentation	Apr 3, 2020	Scene SegmentationScene Understanding	CodeCode Available	1	5
DC-SAM: In-Context Segment Anything in Images and Videos via Dual Consistency	Apr 16, 2025	Few-Shot LearningInteractive Segmentation	CodeCode Available	1	5
Few-Shot Object Detection and Viewpoint Estimation for Objects in the Wild	Jul 23, 2020	Few-Shot Object DetectionMeta-Learning	CodeCode Available	1	5
FreDSNet: Joint Monocular Depth and Semantic Segmentation with Fast Fourier Convolutions	Oct 4, 2022	Depth EstimationMonocular Depth Estimation	CodeCode Available	1	5
General Geometry-aware Weakly Supervised 3D Object Detection	Jul 18, 2024	3D Object DetectionObject	CodeCode Available	1	5
Activation Modulation and Recalibration Scheme for Weakly Supervised Semantic Segmentation	Dec 16, 2021	Feature ImportanceScene Understanding	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