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 1631–1640 of 1723 papers

Title	Date	Tasks	Status
Implicit Background Estimation for Semantic Segmentation	May 23, 2019	Scene UnderstandingSegmentation	CodeCode Available
SceneNet RGB-D: 5M Photorealistic Images of Synthetic Indoor Trajectories with Ground Truth	Dec 15, 2016	3D ReconstructionCamera Pose Estimation	CodeCode Available
Placental Vessel Segmentation and Registration in Fetoscopy: Literature Review and MICCAI FetReg2021 Challenge Findings	Jun 24, 2022	Scene UnderstandingSemantic Segmentation	CodeCode Available
SceneNet: Understanding Real World Indoor Scenes With Synthetic Data	Nov 22, 2015	Scene Understanding	CodeCode Available
Fast Scene Understanding for Autonomous Driving	Aug 8, 2017	Autonomous DrivingDecoder	CodeCode Available
Swiss DINO: Efficient and Versatile Vision Framework for On-device Personal Object Search	Jul 10, 2024	Few-Shot LearningGPU	CodeCode Available
Cognitive Visual Commonsense Reasoning Using Dynamic Working Memory	Jul 4, 2021	Question AnsweringScene Understanding	CodeCode Available
Leveraging Acoustic Images for Effective Self-Supervised Audio Representation Learning	Aug 1, 2020	Cross-Modal RetrievalRepresentation Learning	CodeCode Available
Attend, Infer, Repeat: Fast Scene Understanding with Generative Models	Mar 28, 2016	Scene Understanding	CodeCode Available
A New Lightweight Hybrid Graph Convolutional Neural Network -- CNN Scheme for Scene Classification using Object Detection Inference	Jul 19, 2024	Autonomous Vehiclesobject-detection	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