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
A diffusion and clustering-based approach for finding coherent motions and understanding crowd scenes	Feb 16, 2016	ClusteringOptical Flow Estimation	—Unverified
What Can I Do Around Here? Deep Functional Scene Understanding for Cognitive Robots	Jan 29, 2016	image-classificationImage Classification	—Unverified
COCO-Text: Dataset and Benchmark for Text Detection and Recognition in Natural Images	Jan 26, 2016	DiversityGeneral Classification	CodeCode Available
Car Segmentation and Pose Estimation using 3D Object Models	Dec 21, 2015	3D Pose EstimationImage Segmentation	—Unverified
Galileo: Perceiving Physical Object Properties by Integrating a Physics Engine with Deep Learning	Dec 1, 2015	FrictionScene Understanding	—Unverified
COUNT Forest: CO-Voting Uncertain Number of Targets Using Random Forest for Crowd Density Estimation	Dec 1, 2015	Density EstimationScene Understanding	—Unverified
Exploiting High Level Scene Cues in Stereo Reconstruction	Dec 1, 2015	3D ReconstructionScene Understanding	—Unverified
Single Image 3D Without a Single 3D Image	Dec 1, 2015	Scene Understanding	—Unverified
Pedestrian Travel Time Estimation in Crowded Scenes	Dec 1, 2015	BlockingScene Understanding	—Unverified
SceneNet: Understanding Real World Indoor Scenes With Synthetic Data	Nov 22, 2015	Scene Understanding	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