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 1661–1670 of 1723 papers

Title	Date	Tasks	Status	Hype
Car Segmentation and Pose Estimation using 3D Object Models	Dec 21, 2015	3D Pose EstimationImage Segmentation	—Unverified	0
Single Image 3D Without a Single 3D Image	Dec 1, 2015	Scene Understanding	—Unverified	0
Pedestrian Travel Time Estimation in Crowded Scenes	Dec 1, 2015	BlockingScene Understanding	—Unverified	0
Exploiting High Level Scene Cues in Stereo Reconstruction	Dec 1, 2015	3D ReconstructionScene Understanding	—Unverified	0
COUNT Forest: CO-Voting Uncertain Number of Targets Using Random Forest for Crowd Density Estimation	Dec 1, 2015	Density EstimationScene Understanding	—Unverified	0
Galileo: Perceiving Physical Object Properties by Integrating a Physics Engine with Deep Learning	Dec 1, 2015	FrictionScene Understanding	—Unverified	0
SceneNet: Understanding Real World Indoor Scenes With Synthetic Data	Nov 22, 2015	Scene Understanding	CodeCode Available	0
Semantic Instance Annotation of Street Scenes by 3D to 2D Label Transfer	Nov 10, 2015	Object RecognitionScene Understanding	—Unverified	0
Bayesian SegNet: Model Uncertainty in Deep Convolutional Encoder-Decoder Architectures for Scene Understanding	Nov 9, 2015	Decision MakingDecoder	CodeCode Available	1
SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation	Nov 2, 2015	Crowd CountingDecoder	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