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 391–400 of 1723 papers

Title	Date	Tasks	Status	Hype
4D Panoptic LiDAR Segmentation	Feb 24, 2021	4D Panoptic SegmentationBenchmarking	CodeCode Available	1
RGB-D Railway Platform Monitoring and Scene Understanding for Enhanced Passenger Safety	Feb 23, 2021	Multi-Object TrackingMultiview Detection	CodeCode Available	1
Weakly Supervised Learning of Rigid 3D Scene Flow	Feb 17, 2021	Autonomous DrivingScene Flow Estimation	CodeCode Available	1
A2-FPN for Semantic Segmentation of Fine-Resolution Remotely Sensed Images	Feb 16, 2021	Decision MakingScene Understanding	CodeCode Available	1
Single-Shot Cuboids: Geodesics-based End-to-end Manhattan Aligned Layout Estimation from Spherical Panoramas	Feb 7, 2021	Keypoint EstimationScene Understanding	CodeCode Available	1
OpenGF: An Ultra-Large-Scale Ground Filtering Dataset Built Upon Open ALS Point Clouds Around the World	Jan 24, 2021	3D Semantic SegmentationDeep Learning	CodeCode Available	1
Automatic Extrinsic Calibration Method for LiDAR and Camera Sensor Setups	Jan 12, 2021	Scene Understanding	CodeCode Available	1
Grounding Consistency: Distilling Spatial Common Sense for Precise Visual Relationship Detection	Jan 1, 2021	Common Sense ReasoningGraph Generation	CodeCode Available	1
Exploring Data-Efficient 3D Scene Understanding with Contrastive Scene Contexts	Dec 16, 2020	3D Semantic SegmentationInstance Segmentation	CodeCode Available	1
Event-based Motion Segmentation with Spatio-Temporal Graph Cuts	Dec 16, 2020	Motion SegmentationScene Understanding	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