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 1201–1210 of 1723 papers

Title	Date	Tasks	Status	Hype
Scale-aware Neural Network for Semantic Segmentation of Multi-resolution Remote Sensing Images	Mar 14, 2021	Scene UnderstandingSegmentation	—Unverified	0
Monte Carlo Scene Search for 3D Scene Understanding	Mar 14, 2021	Scene Understanding	CodeCode Available	1
Affect2MM: Affective Analysis of Multimedia Content Using Emotion Causality	Mar 11, 2021	Scene UnderstandingTime Series	CodeCode Available	1
Holistic 3D Scene Understanding from a Single Image with Implicit Representation	Mar 11, 2021	3D Object Detection3D Shape Reconstruction	CodeCode Available	1
Exploiting Edge-Oriented Reasoning for 3D Point-based Scene Graph Analysis	Mar 9, 2021	3d scene graph generationgraph construction	CodeCode Available	1
Fine-Grained Off-Road Semantic Segmentation and Mapping via Contrastive Learning	Mar 5, 2021	Binary ClassificationContrastive Learning	—Unverified	0
Multimodal Scale Consistency and Awareness for Monocular Self-Supervised Depth Estimation	Mar 3, 2021	Autonomous DrivingDepth Estimation	CodeCode Available	0
Simulation-to-Real domain adaptation with teacher-student learning for endoscopic instrument segmentation	Mar 2, 2021	Domain AdaptationScene Understanding	—Unverified	0
FPS-Net: A Convolutional Fusion Network for Large-Scale LiDAR Point Cloud Segmentation	Mar 1, 2021	3D Semantic SegmentationDecoder	CodeCode Available	1
Panoramic Panoptic Segmentation: Towards Complete Surrounding Understanding via Unsupervised Contrastive Learning	Mar 1, 2021	Contrastive LearningPanoptic Segmentation	CodeCode Available	1

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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